{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "Credit=pd.read_csv(\"Credit.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#SOME QUICK STATS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>LIMIT_BAL</th>\n",
       "      <th>SEX</th>\n",
       "      <th>EDUCATION</th>\n",
       "      <th>MARRIAGE</th>\n",
       "      <th>AGE</th>\n",
       "      <th>PAY_0</th>\n",
       "      <th>PAY_2</th>\n",
       "      <th>PAY_3</th>\n",
       "      <th>PAY_4</th>\n",
       "      <th>...</th>\n",
       "      <th>BILL_AMT4</th>\n",
       "      <th>BILL_AMT5</th>\n",
       "      <th>BILL_AMT6</th>\n",
       "      <th>PAY_AMT1</th>\n",
       "      <th>PAY_AMT2</th>\n",
       "      <th>PAY_AMT3</th>\n",
       "      <th>PAY_AMT4</th>\n",
       "      <th>PAY_AMT5</th>\n",
       "      <th>PAY_AMT6</th>\n",
       "      <th>default.payment.next.month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
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       "      <td>689.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>120000.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>26</td>\n",
       "      <td>-1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>3272.0</td>\n",
       "      <td>3455.0</td>\n",
       "      <td>3261.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>90000.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>34</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>14331.0</td>\n",
       "      <td>14948.0</td>\n",
       "      <td>15549.0</td>\n",
       "      <td>1518.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>37</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>28314.0</td>\n",
       "      <td>28959.0</td>\n",
       "      <td>29547.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>1069.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>57</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>20940.0</td>\n",
       "      <td>19146.0</td>\n",
       "      <td>19131.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>36681.0</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>9000.0</td>\n",
       "      <td>689.0</td>\n",
       "      <td>679.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>37</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>19394.0</td>\n",
       "      <td>19619.0</td>\n",
       "      <td>20024.0</td>\n",
       "      <td>2500.0</td>\n",
       "      <td>1815.0</td>\n",
       "      <td>657.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>800.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>500000.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>542653.0</td>\n",
       "      <td>483003.0</td>\n",
       "      <td>473944.0</td>\n",
       "      <td>55000.0</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>38000.0</td>\n",
       "      <td>20239.0</td>\n",
       "      <td>13750.0</td>\n",
       "      <td>13770.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>100000.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>221.0</td>\n",
       "      <td>-159.0</td>\n",
       "      <td>567.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>601.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>581.0</td>\n",
       "      <td>1687.0</td>\n",
       "      <td>1542.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>140000.0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>12211.0</td>\n",
       "      <td>11793.0</td>\n",
       "      <td>3719.0</td>\n",
       "      <td>3329.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>432.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>35</td>\n",
       "      <td>-2</td>\n",
       "      <td>-2</td>\n",
       "      <td>-2</td>\n",
       "      <td>-2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13007.0</td>\n",
       "      <td>13912.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13007.0</td>\n",
       "      <td>1122.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID  LIMIT_BAL  SEX  EDUCATION  MARRIAGE  AGE  PAY_0  PAY_2  PAY_3  PAY_4  \\\n",
       "0   1    20000.0    2          2         1   24      2      2     -1     -1   \n",
       "1   2   120000.0    2          2         2   26     -1      2      0      0   \n",
       "2   3    90000.0    2          2         2   34      0      0      0      0   \n",
       "3   4    50000.0    2          2         1   37      0      0      0      0   \n",
       "4   5    50000.0    1          2         1   57     -1      0     -1      0   \n",
       "5   6    50000.0    1          1         2   37      0      0      0      0   \n",
       "6   7   500000.0    1          1         2   29      0      0      0      0   \n",
       "7   8   100000.0    2          2         2   23      0     -1     -1      0   \n",
       "8   9   140000.0    2          3         1   28      0      0      2      0   \n",
       "9  10    20000.0    1          3         2   35     -2     -2     -2     -2   \n",
       "\n",
       "              ...              BILL_AMT4  BILL_AMT5  BILL_AMT6  PAY_AMT1  \\\n",
       "0             ...                    0.0        0.0        0.0       0.0   \n",
       "1             ...                 3272.0     3455.0     3261.0       0.0   \n",
       "2             ...                14331.0    14948.0    15549.0    1518.0   \n",
       "3             ...                28314.0    28959.0    29547.0    2000.0   \n",
       "4             ...                20940.0    19146.0    19131.0    2000.0   \n",
       "5             ...                19394.0    19619.0    20024.0    2500.0   \n",
       "6             ...               542653.0   483003.0   473944.0   55000.0   \n",
       "7             ...                  221.0     -159.0      567.0     380.0   \n",
       "8             ...                12211.0    11793.0     3719.0    3329.0   \n",
       "9             ...                    0.0    13007.0    13912.0       0.0   \n",
       "\n",
       "   PAY_AMT2  PAY_AMT3  PAY_AMT4  PAY_AMT5  PAY_AMT6  \\\n",
       "0     689.0       0.0       0.0       0.0       0.0   \n",
       "1    1000.0    1000.0    1000.0       0.0    2000.0   \n",
       "2    1500.0    1000.0    1000.0    1000.0    5000.0   \n",
       "3    2019.0    1200.0    1100.0    1069.0    1000.0   \n",
       "4   36681.0   10000.0    9000.0     689.0     679.0   \n",
       "5    1815.0     657.0    1000.0    1000.0     800.0   \n",
       "6   40000.0   38000.0   20239.0   13750.0   13770.0   \n",
       "7     601.0       0.0     581.0    1687.0    1542.0   \n",
       "8       0.0     432.0    1000.0    1000.0    1000.0   \n",
       "9       0.0       0.0   13007.0    1122.0       0.0   \n",
       "\n",
       "   default.payment.next.month  \n",
       "0                           1  \n",
       "1                           1  \n",
       "2                           0  \n",
       "3                           0  \n",
       "4                           0  \n",
       "5                           0  \n",
       "6                           0  \n",
       "7                           0  \n",
       "8                           0  \n",
       "9                           0  \n",
       "\n",
       "[10 rows x 25 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Credit.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>15000.500000</td>\n",
       "      <td>8660.398374</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7500.75</td>\n",
       "      <td>15000.5</td>\n",
       "      <td>22500.25</td>\n",
       "      <td>30000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LIMIT_BAL</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>167484.322667</td>\n",
       "      <td>129747.661567</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>50000.00</td>\n",
       "      <td>140000.0</td>\n",
       "      <td>240000.00</td>\n",
       "      <td>1000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SEX</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>1.603733</td>\n",
       "      <td>0.489129</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EDUCATION</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>1.853133</td>\n",
       "      <td>0.790349</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MARRIAGE</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>1.551867</td>\n",
       "      <td>0.521970</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AGE</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>35.485500</td>\n",
       "      <td>9.217904</td>\n",
       "      <td>21.0</td>\n",
       "      <td>28.00</td>\n",
       "      <td>34.0</td>\n",
       "      <td>41.00</td>\n",
       "      <td>79.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_0</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>-0.016700</td>\n",
       "      <td>1.123802</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>-1.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_2</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>-0.133767</td>\n",
       "      <td>1.197186</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>-1.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_3</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>-0.166200</td>\n",
       "      <td>1.196868</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>-1.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_4</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>-0.220667</td>\n",
       "      <td>1.169139</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>-1.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_5</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>-0.266200</td>\n",
       "      <td>1.133187</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>-1.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_6</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>-0.291100</td>\n",
       "      <td>1.149988</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>-1.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILL_AMT1</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>51223.330900</td>\n",
       "      <td>73635.860576</td>\n",
       "      <td>-165580.0</td>\n",
       "      <td>3558.75</td>\n",
       "      <td>22381.5</td>\n",
       "      <td>67091.00</td>\n",
       "      <td>964511.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILL_AMT2</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>49179.075167</td>\n",
       "      <td>71173.768783</td>\n",
       "      <td>-69777.0</td>\n",
       "      <td>2984.75</td>\n",
       "      <td>21200.0</td>\n",
       "      <td>64006.25</td>\n",
       "      <td>983931.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILL_AMT3</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>47013.154800</td>\n",
       "      <td>69349.387427</td>\n",
       "      <td>-157264.0</td>\n",
       "      <td>2666.25</td>\n",
       "      <td>20088.5</td>\n",
       "      <td>60164.75</td>\n",
       "      <td>1664089.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILL_AMT4</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>43262.948967</td>\n",
       "      <td>64332.856134</td>\n",
       "      <td>-170000.0</td>\n",
       "      <td>2326.75</td>\n",
       "      <td>19052.0</td>\n",
       "      <td>54506.00</td>\n",
       "      <td>891586.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILL_AMT5</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>40311.400967</td>\n",
       "      <td>60797.155770</td>\n",
       "      <td>-81334.0</td>\n",
       "      <td>1763.00</td>\n",
       "      <td>18104.5</td>\n",
       "      <td>50190.50</td>\n",
       "      <td>927171.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILL_AMT6</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>38871.760400</td>\n",
       "      <td>59554.107537</td>\n",
       "      <td>-339603.0</td>\n",
       "      <td>1256.00</td>\n",
       "      <td>17071.0</td>\n",
       "      <td>49198.25</td>\n",
       "      <td>961664.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_AMT1</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>5663.580500</td>\n",
       "      <td>16563.280354</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.00</td>\n",
       "      <td>2100.0</td>\n",
       "      <td>5006.00</td>\n",
       "      <td>873552.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_AMT2</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>5921.163500</td>\n",
       "      <td>23040.870402</td>\n",
       "      <td>0.0</td>\n",
       "      <td>833.00</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>5000.00</td>\n",
       "      <td>1684259.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_AMT3</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>5225.681500</td>\n",
       "      <td>17606.961470</td>\n",
       "      <td>0.0</td>\n",
       "      <td>390.00</td>\n",
       "      <td>1800.0</td>\n",
       "      <td>4505.00</td>\n",
       "      <td>896040.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_AMT4</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>4826.076867</td>\n",
       "      <td>15666.159744</td>\n",
       "      <td>0.0</td>\n",
       "      <td>296.00</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>4013.25</td>\n",
       "      <td>621000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_AMT5</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>4799.387633</td>\n",
       "      <td>15278.305679</td>\n",
       "      <td>0.0</td>\n",
       "      <td>252.50</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>4031.50</td>\n",
       "      <td>426529.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_AMT6</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>5215.502567</td>\n",
       "      <td>17777.465775</td>\n",
       "      <td>0.0</td>\n",
       "      <td>117.75</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>4000.00</td>\n",
       "      <td>528666.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>default.payment.next.month</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>0.221200</td>\n",
       "      <td>0.415062</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              count           mean            std       min  \\\n",
       "ID                          30000.0   15000.500000    8660.398374       1.0   \n",
       "LIMIT_BAL                   30000.0  167484.322667  129747.661567   10000.0   \n",
       "SEX                         30000.0       1.603733       0.489129       1.0   \n",
       "EDUCATION                   30000.0       1.853133       0.790349       0.0   \n",
       "MARRIAGE                    30000.0       1.551867       0.521970       0.0   \n",
       "AGE                         30000.0      35.485500       9.217904      21.0   \n",
       "PAY_0                       30000.0      -0.016700       1.123802      -2.0   \n",
       "PAY_2                       30000.0      -0.133767       1.197186      -2.0   \n",
       "PAY_3                       30000.0      -0.166200       1.196868      -2.0   \n",
       "PAY_4                       30000.0      -0.220667       1.169139      -2.0   \n",
       "PAY_5                       30000.0      -0.266200       1.133187      -2.0   \n",
       "PAY_6                       30000.0      -0.291100       1.149988      -2.0   \n",
       "BILL_AMT1                   30000.0   51223.330900   73635.860576 -165580.0   \n",
       "BILL_AMT2                   30000.0   49179.075167   71173.768783  -69777.0   \n",
       "BILL_AMT3                   30000.0   47013.154800   69349.387427 -157264.0   \n",
       "BILL_AMT4                   30000.0   43262.948967   64332.856134 -170000.0   \n",
       "BILL_AMT5                   30000.0   40311.400967   60797.155770  -81334.0   \n",
       "BILL_AMT6                   30000.0   38871.760400   59554.107537 -339603.0   \n",
       "PAY_AMT1                    30000.0    5663.580500   16563.280354       0.0   \n",
       "PAY_AMT2                    30000.0    5921.163500   23040.870402       0.0   \n",
       "PAY_AMT3                    30000.0    5225.681500   17606.961470       0.0   \n",
       "PAY_AMT4                    30000.0    4826.076867   15666.159744       0.0   \n",
       "PAY_AMT5                    30000.0    4799.387633   15278.305679       0.0   \n",
       "PAY_AMT6                    30000.0    5215.502567   17777.465775       0.0   \n",
       "default.payment.next.month  30000.0       0.221200       0.415062       0.0   \n",
       "\n",
       "                                 25%       50%        75%        max  \n",
       "ID                           7500.75   15000.5   22500.25    30000.0  \n",
       "LIMIT_BAL                   50000.00  140000.0  240000.00  1000000.0  \n",
       "SEX                             1.00       2.0       2.00        2.0  \n",
       "EDUCATION                       1.00       2.0       2.00        6.0  \n",
       "MARRIAGE                        1.00       2.0       2.00        3.0  \n",
       "AGE                            28.00      34.0      41.00       79.0  \n",
       "PAY_0                          -1.00       0.0       0.00        8.0  \n",
       "PAY_2                          -1.00       0.0       0.00        8.0  \n",
       "PAY_3                          -1.00       0.0       0.00        8.0  \n",
       "PAY_4                          -1.00       0.0       0.00        8.0  \n",
       "PAY_5                          -1.00       0.0       0.00        8.0  \n",
       "PAY_6                          -1.00       0.0       0.00        8.0  \n",
       "BILL_AMT1                    3558.75   22381.5   67091.00   964511.0  \n",
       "BILL_AMT2                    2984.75   21200.0   64006.25   983931.0  \n",
       "BILL_AMT3                    2666.25   20088.5   60164.75  1664089.0  \n",
       "BILL_AMT4                    2326.75   19052.0   54506.00   891586.0  \n",
       "BILL_AMT5                    1763.00   18104.5   50190.50   927171.0  \n",
       "BILL_AMT6                    1256.00   17071.0   49198.25   961664.0  \n",
       "PAY_AMT1                     1000.00    2100.0    5006.00   873552.0  \n",
       "PAY_AMT2                      833.00    2009.0    5000.00  1684259.0  \n",
       "PAY_AMT3                      390.00    1800.0    4505.00   896040.0  \n",
       "PAY_AMT4                      296.00    1500.0    4013.25   621000.0  \n",
       "PAY_AMT5                      252.50    1500.0    4031.50   426529.0  \n",
       "PAY_AMT6                      117.75    1500.0    4000.00   528666.0  \n",
       "default.payment.next.month      0.00       0.0       0.00        1.0  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Credit.describe().transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count      30000.000000\n",
       "mean      167484.322667\n",
       "std       129747.661567\n",
       "min        10000.000000\n",
       "25%        50000.000000\n",
       "50%       140000.000000\n",
       "75%       240000.000000\n",
       "max      1000000.000000\n",
       "Name: LIMIT_BAL, dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Credit['LIMIT_BAL'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2    18112\n",
       "1    11888\n",
       "Name: SEX, dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Credit['SEX'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2    14030\n",
       "1    10585\n",
       "3     4917\n",
       "5      280\n",
       "4      123\n",
       "6       51\n",
       "0       14\n",
       "Name: EDUCATION, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Credit['EDUCATION'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2    15964\n",
       "1    13659\n",
       "3      323\n",
       "0       54\n",
       "Name: MARRIAGE, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Credit['MARRIAGE'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    30000.000000\n",
       "mean        35.485500\n",
       "std          9.217904\n",
       "min         21.000000\n",
       "25%         28.000000\n",
       "50%         34.000000\n",
       "75%         41.000000\n",
       "max         79.000000\n",
       "Name: AGE, dtype: float64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Credit['AGE'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 0    14737\n",
      "-1     5686\n",
      " 1     3688\n",
      "-2     2759\n",
      " 2     2667\n",
      " 3      322\n",
      " 4       76\n",
      " 5       26\n",
      " 8       19\n",
      " 6       11\n",
      " 7        9\n",
      "Name: PAY_0, dtype: int64  0    15730\n",
      "-1     6050\n",
      " 2     3927\n",
      "-2     3782\n",
      " 3      326\n",
      " 4       99\n",
      " 1       28\n",
      " 5       25\n",
      " 7       20\n",
      " 6       12\n",
      " 8        1\n",
      "Name: PAY_2, dtype: int64  0    15764\n",
      "-1     5938\n",
      "-2     4085\n",
      " 2     3819\n",
      " 3      240\n",
      " 4       76\n",
      " 7       27\n",
      " 6       23\n",
      " 5       21\n",
      " 1        4\n",
      " 8        3\n",
      "Name: PAY_3, dtype: int64  0    16455\n",
      "-1     5687\n",
      "-2     4348\n",
      " 2     3159\n",
      " 3      180\n",
      " 4       69\n",
      " 7       58\n",
      " 5       35\n",
      " 6        5\n",
      " 8        2\n",
      " 1        2\n",
      "Name: PAY_4, dtype: int64  0    16947\n",
      "-1     5539\n",
      "-2     4546\n",
      " 2     2626\n",
      " 3      178\n",
      " 4       84\n",
      " 7       58\n",
      " 5       17\n",
      " 6        4\n",
      " 8        1\n",
      "Name: PAY_5, dtype: int64  0    16286\n",
      "-1     5740\n",
      "-2     4895\n",
      " 2     2766\n",
      " 3      184\n",
      " 4       49\n",
      " 7       46\n",
      " 6       19\n",
      " 5       13\n",
      " 8        2\n",
      "Name: PAY_6, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "pay0=Credit['PAY_0'].value_counts()\n",
    "pay2=Credit['PAY_2'].value_counts()\n",
    "pay3=Credit['PAY_3'].value_counts()\n",
    "pay4=Credit['PAY_4'].value_counts()\n",
    "pay5=Credit['PAY_5'].value_counts()\n",
    "pay6=Credit['PAY_6'].value_counts()\n",
    "print(pay0,pay1,pay3,pay4,pay5,pay6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ID                            0\n",
       "LIMIT_BAL                     0\n",
       "SEX                           0\n",
       "EDUCATION                     0\n",
       "MARRIAGE                      0\n",
       "AGE                           0\n",
       "PAY_0                         0\n",
       "PAY_2                         0\n",
       "PAY_3                         0\n",
       "PAY_4                         0\n",
       "PAY_5                         0\n",
       "PAY_6                         0\n",
       "BILL_AMT1                     0\n",
       "BILL_AMT2                     0\n",
       "BILL_AMT3                     0\n",
       "BILL_AMT4                     0\n",
       "BILL_AMT5                     0\n",
       "BILL_AMT6                     0\n",
       "PAY_AMT1                      0\n",
       "PAY_AMT2                      0\n",
       "PAY_AMT3                      0\n",
       "PAY_AMT4                      0\n",
       "PAY_AMT5                      0\n",
       "PAY_AMT6                      0\n",
       "default.payment.next.month    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Credit.apply(lambda x: sum(x.isnull()),axis=0) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#VISUALIZATION ANALYSIS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import seaborn as sb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1cba191eeb8>"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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94xvfUH19vUpKSqjjCBUVFekvf/mLjDE6ceKEPvnkE918883UcYRycnJSYfmV\nr3xFZ8+e5d/1GEx07b5sH8ORNncm41alA23evFl/+MMflJ+fn2p7+OGHtXnzZvX19Sk/P1+bN29W\nZmamWltb9corr8gYoxUrVqi0tFSffPKJqqurFY1GlZWVpYaGBgUCAb333nvasmWLzp07p3nz5qmq\nqkqStGPHDrW1tam/v18bNmxQcXHxZE193JSVlenRRx9VRkaGamtrqeMI/fSnP9XBgwdljFFVVZWu\nuOIK6jhCiURCNTU1ikaj6uvr0w9+8APNnj2bOo7Ahx9+qAcffFCtra06evTohNbu5MmTqq6uViKR\nUG5urhoaGjR9+vQhx5w2QQ0AQDpKm1PfAACkI4IaAACLEdQAAFiMoAYAwGIENQAAFiOoAQCwGEEN\nAIDFCGoAACz2f9GIEj39bnr0AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cba168e1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Limit Bal distribution\n",
    "Credit['LIMIT_BAL'].hist(bins=60, color='orange')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1cba1684ef0>"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cb9f8d2518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#prediction labels\n",
    "Credit.groupby('default.payment.next.month').size().plot(kind='bar', color='yellow')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1e1bbbdb080>"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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LpYiICEmSzWaT0+mUy+WS3W737s9ms+nIkSMKDw9Xo0aNqrU7nc6LhoGoqKsVGuqH507r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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1e1bd6097f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#default payment vs Limi_bal wrt gender\n",
    "sb.barplot(x=\"default.payment.next.month\",y=\"LIMIT_BAL\", hue=\"SEX\", data=Credit, palette=\"Blues\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1cba309e5c0>"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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7uySf2759u5KSkvxdhs/V1tZqypQpSkxM1PDhw7VmzRp/l+RTZ8+e1dSpUzVq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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cba2d87c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Education levels count vs default payments\n",
    "sb.countplot(x=\"EDUCATION\", hue=\"default.payment.next.month\", data=Credit, palette=\"Set2\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1e1bdef45f8>"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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++yVJlmUpMTExxhPhTNx4443hF2qffPKJUlNTYzxRdPGpNnHqTD+ZEOeWvLw8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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1e1bdf96898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Marriage levels count\n",
    "sb.countplot(x=\"MARRIAGE\", data=Credit, palette=\"Set2\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1e1bfc9a630>"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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iU6dOKTs72/v38dOmTdOcOXOUlZWlmJgYJSYmym63KzU1VSkpKbIsS5MmTVKr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\nAGCI/wfZW8Acv/LfMQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1e1bf9ca940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Marriage levels vs defaul payments\n",
    "sb.countplot(x=\"MARRIAGE\", hue=\"default.payment.next.month\", data=Credit, palette=\"bright\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1e1bfd59668>"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Tv39/HTp0SGPHjlVzc7NWrFgR8XOy0+/Gk08+qfz8fOXn56uzs1MlJSXaunWr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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1e1bfbe2ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#aLL Pay distributions\n",
    "sb.countplot(x=\"PAY_0\", data=Credit,palette=\"Purples_r\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1cbcf48ada0>"
      ]
     },
     "execution_count": 201,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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WrlwZ8f8XiX4fdXR0aP369Xr77bc1bNgwPfvss6qtrY25v3B//etfq7i4WGfO\nnIn2KFcYLHdT3Lp1q3bt2qVhw4ZFe5Qr7Nq1SykpKXrppZf0hz/8QTk5OTH3/2Btba0kqbq6WgcO\nHNC6deti7r9zKBRSUVGRrrvuumiP8pWCwaAsy4q5bzq/7MCBA/rVr36lqqoqXbx4UT/+8Y+jPdIV\nZs+erdmzZ0uSVqxYoe9973sxE3xJqqurU1dXl6qrq9XQ0KD169drw4YNET1m7F2mxii73a7q6upw\nCLq6upSUlBTlqa7U2dmpV155RWlpadEe5QqD5W6KqampEf/C+2PNmDFDf/u3fytJsixL8fHxUZ7o\nSvfdd59WrlwpSfrkk09i6i/Zy9auXau5c+dqzJgx0R7lKzU3N+vixYt64okn9Mgjj6ipqSnaI11h\n7969crvdeuaZZ/T000/rW9/6VrRHuqpf//rX+v3vf6+HH3442qP0MG7cOHV3d+vSpUvy+/0Dcs8Z\nrvT7KC4uTn/2Z1/czrKiokIXLlzQXXfdFeWprpSZmRntEa7K7/eHn66UpPj4eHV1dcXczZWys7N1\n8uTJaI/xlRwOh6Qv/iwXLlyoRYsWRXmir5aQkKCCggL9/Oc/18svvxztcXp44403NGrUKE2dOlVb\ntmyJ9jhf6brrrtOTTz6pOXPm6KOPPtK8efP07rvvxtTXSltbmz755BNt2rRJJ0+eVF5ent59913Z\nbLZoj3aFzZs365lnnon2GFcYPny4Tp06pZkzZ6qtrU2bNm2K+DG50u/FunXr5PP55PP51N3drbVr\n16qhoUEbNmyImf+5/++MsYq7KfaP06dP65FHHtGsWbP04IMPRnucq1q7dq3ee+89LV++XBcuXIj2\nOGE7d+7Uvn375PP59OGHH6qgoECtra3RHquHcePG6Tvf+Y5sNpvGjRunlJSUmJsxJSVFWVlZstvt\nSktLU1JSks6fPx/tsa7w+eef69ixY5oyZUq0R7nCa6+9pqysLL333nt66623tGTJEgWDwYgek79x\ne5Gfnx9+u7CwUHa7XeXl5TH1Ar4vzxjLMjIyVFtbqwceeIC7Kf6Rzp49qyeeeEJFRUW68847oz3O\nV3rzzTd15swZ/eAHP9CwYcNks9li6uvlpz/9afhtn8+nkpISjR49OooTXWnHjh367W9/q5KSEp05\nc0Z+vz/mZszMzNQ//uM/6vHHH9dnn32mixcvKiUlJdpjXeHgwYMx+7WSnJysxMRESdKIESPU1dUV\n8Qs3ot9cDjWwAAADhElEQVRHR44c0Y4dOzRp0iQ9+uijkqRHHnlE999/f5QnGzzuv/9+NTQ0aO7c\nueG7KeLabNq0SZ9//rnKy8tVXl4u6YsXHsbSC9K+/e1v64UXXtD3v/99dXV1aenSpTE132Dw0EMP\n6YUXXpDH45HNZtOLL74Yc8+KTZ8+XQcPHtRDDz0ky7JUVFQUk68xOXbsmMaOHRvtMb7SY489pqVL\nl8rr9SoUCik/P1/Dhw+P6DG5Ix8AAIaInefcAABARBF9AAAMQfQBADAE0QcAwBBEHwAAQxB9AF/p\n5MmTuu222zRr1izl5OTor//6r/X444/r008/De/53ve+p6effjr8uKurSzk5Odq+fXuPz1VWVqaF\nCxd+7fF2796tWbNm6Tvf+Y7mz5+v//7v/+7fEwJA9AFc3ZgxY/TWW2/pzTff1DvvvKPbbrstfF/9\n3/zmN0pMTFRzc7NOnz4t6Yvb77744ovasGFD+Jc+NTc3680331RJSclVj+P3+1VSUqItW7Zo165d\n+uY3vxmzv/8AGMyIPoA+mzRpkj766CNJX9zD/q677tK9996rmpqa8J7x48fL4/Fo5cqVunTpkgoL\nC1VUVKRRo0Zd9fOGQiGVlJTo+uuvlyR985vfDH8jAaD/EH0AfRIKhfSv//qvysjIUCgU0q5duzRz\n5kzNnDlTO3bsUFdXV3jv/Pnz9dFHH2nx4sW66aabdN99933t5x45cmR4T0dHh7Zs2dLrxwC4drF1\nX0cAMeWzzz7TrFmzJH3xa5vT09P13HPPqa6uTqNHj9bNN98sy7IUFxen2tra8G2p7Xa7ioqKNH/+\nfNXW1vb5eO3t7Zo/f75uvfVWffe7343IOQEmI/oAruryz/T/r507d+r06dO65557JH3xM/nq6uoe\nv4viz//8z5WcnCyXy9WnY3322Wd68sknNWXKFC1durR/TgBAD0QfwDU5e/asGhoa9POf/zz8M/gT\nJ05oxowZOnHihG644YZr/pzd3d16+umnNXPmTM2fP7+/RwbwP/iZPoBrsmvXLt19993h4EvSDTfc\noHvuuUevv/76H/U533//fR09elTvvfeeZs2apVmzZmnZsmX9NTKA/8Fv2QMAwBA8vQ9gQHR0dOjh\nhx/+yvctXLhQ99577wBPBJiHK30AAAzBz/QBADAE0QcAwBBEHwAAQxB9AAAMQfQBADAE0QcAwBD/\nH/3b0oWWkcJKAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cbcb1988d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.countplot(x=\"PAY_2\", data=Credit,palette=(\"Purples_r\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1cbc6201668>"
      ]
     },
     "execution_count": 202,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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nZ6cWLFigM2fOyOFwaM2aNdw7AACAARpQ9Juamvo8HjlypNauXXvVO6uvr1dPT49qamrU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\nzwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cbcf4aa710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.countplot(x=\"PAY_3\", data=Credit,palette=\"Purples_r\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1cbaae1f9b0>"
      ]
     },
     "execution_count": 204,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Kf5h6e3u1bt06vfnmm0pJSdHTTz+tpqammPuB+6c//UkVFRU6efJktKNc5PN3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\nAGCI/wcHydOonBuRAgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cbc63d4b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.countplot(x=\"PAY_4\", data=Credit,palette=\"Purples_r\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1cbcb0e82b0>"
      ]
     },
     "execution_count": 205,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ZM4qLi1N5eXnEfpYp/evU09OjzZs36+2339aYMWP0/e9/X42NjSP+H/hf/epX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\nAAAM8X8BBbTPjXkcHkkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cbc9ea0fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.countplot(x=\"PAY_5\", data=Credit,palette=\"Purples_r\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1cbc8d82c50>"
      ]
     },
     "execution_count": 206,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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mm0pKStI//uM/qqmpadT/A//LX/5SFRUVOn36dKSjDOnzuy62tbVp/fr1ev75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\nEJQ+AACG+D9SWsPRY75eSwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1cbcf4404e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.countplot(x=\"PAY_6\", data=Credit,palette=\"Purples_r\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Some Extra VISUALIZATIONS(NOT PART OF THE REPORT)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#lets calucate correlation matrix\n",
    "corr=Credit.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>LIMIT_BAL</th>\n",
       "      <th>SEX</th>\n",
       "      <th>EDUCATION</th>\n",
       "      <th>MARRIAGE</th>\n",
       "      <th>AGE</th>\n",
       "      <th>PAY_0</th>\n",
       "      <th>PAY_2</th>\n",
       "      <th>PAY_3</th>\n",
       "      <th>PAY_4</th>\n",
       "      <th>...</th>\n",
       "      <th>BILL_AMT4</th>\n",
       "      <th>BILL_AMT5</th>\n",
       "      <th>BILL_AMT6</th>\n",
       "      <th>PAY_AMT1</th>\n",
       "      <th>PAY_AMT2</th>\n",
       "      <th>PAY_AMT3</th>\n",
       "      <th>PAY_AMT4</th>\n",
       "      <th>PAY_AMT5</th>\n",
       "      <th>PAY_AMT6</th>\n",
       "      <th>default.payment.next.month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.026179</td>\n",
       "      <td>0.018497</td>\n",
       "      <td>0.039177</td>\n",
       "      <td>-0.029079</td>\n",
       "      <td>0.018678</td>\n",
       "      <td>-0.030575</td>\n",
       "      <td>-0.011215</td>\n",
       "      <td>-0.018494</td>\n",
       "      <td>-0.002735</td>\n",
       "      <td>...</td>\n",
       "      <td>0.040351</td>\n",
       "      <td>0.016705</td>\n",
       "      <td>0.016730</td>\n",
       "      <td>0.009742</td>\n",
       "      <td>0.008406</td>\n",
       "      <td>0.039151</td>\n",
       "      <td>0.007793</td>\n",
       "      <td>0.000652</td>\n",
       "      <td>0.003000</td>\n",
       "      <td>-0.013952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LIMIT_BAL</th>\n",
       "      <td>0.026179</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.024755</td>\n",
       "      <td>-0.219161</td>\n",
       "      <td>-0.108139</td>\n",
       "      <td>0.144713</td>\n",
       "      <td>-0.271214</td>\n",
       "      <td>-0.296382</td>\n",
       "      <td>-0.286123</td>\n",
       "      <td>-0.267460</td>\n",
       "      <td>...</td>\n",
       "      <td>0.293988</td>\n",
       "      <td>0.295562</td>\n",
       "      <td>0.290389</td>\n",
       "      <td>0.195236</td>\n",
       "      <td>0.178408</td>\n",
       "      <td>0.210167</td>\n",
       "      <td>0.203242</td>\n",
       "      <td>0.217202</td>\n",
       "      <td>0.219595</td>\n",
       "      <td>-0.153520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SEX</th>\n",
       "      <td>0.018497</td>\n",
       "      <td>0.024755</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.014232</td>\n",
       "      <td>-0.031389</td>\n",
       "      <td>-0.090874</td>\n",
       "      <td>-0.057643</td>\n",
       "      <td>-0.070771</td>\n",
       "      <td>-0.066096</td>\n",
       "      <td>-0.060173</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.021880</td>\n",
       "      <td>-0.017005</td>\n",
       "      <td>-0.016733</td>\n",
       "      <td>-0.000242</td>\n",
       "      <td>-0.001391</td>\n",
       "      <td>-0.008597</td>\n",
       "      <td>-0.002229</td>\n",
       "      <td>-0.001667</td>\n",
       "      <td>-0.002766</td>\n",
       "      <td>-0.039961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EDUCATION</th>\n",
       "      <td>0.039177</td>\n",
       "      <td>-0.219161</td>\n",
       "      <td>0.014232</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.143464</td>\n",
       "      <td>0.175061</td>\n",
       "      <td>0.105364</td>\n",
       "      <td>0.121566</td>\n",
       "      <td>0.114025</td>\n",
       "      <td>0.108793</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000451</td>\n",
       "      <td>-0.007567</td>\n",
       "      <td>-0.009099</td>\n",
       "      <td>-0.037456</td>\n",
       "      <td>-0.030038</td>\n",
       "      <td>-0.039943</td>\n",
       "      <td>-0.038218</td>\n",
       "      <td>-0.040358</td>\n",
       "      <td>-0.037200</td>\n",
       "      <td>0.028006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MARRIAGE</th>\n",
       "      <td>-0.029079</td>\n",
       "      <td>-0.108139</td>\n",
       "      <td>-0.031389</td>\n",
       "      <td>-0.143464</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.414170</td>\n",
       "      <td>0.019917</td>\n",
       "      <td>0.024199</td>\n",
       "      <td>0.032688</td>\n",
       "      <td>0.033122</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.023344</td>\n",
       "      <td>-0.025393</td>\n",
       "      <td>-0.021207</td>\n",
       "      <td>-0.005979</td>\n",
       "      <td>-0.008093</td>\n",
       "      <td>-0.003541</td>\n",
       "      <td>-0.012659</td>\n",
       "      <td>-0.001205</td>\n",
       "      <td>-0.006641</td>\n",
       "      <td>-0.024339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AGE</th>\n",
       "      <td>0.018678</td>\n",
       "      <td>0.144713</td>\n",
       "      <td>-0.090874</td>\n",
       "      <td>0.175061</td>\n",
       "      <td>-0.414170</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.039447</td>\n",
       "      <td>-0.050148</td>\n",
       "      <td>-0.053048</td>\n",
       "      <td>-0.049722</td>\n",
       "      <td>...</td>\n",
       "      <td>0.051353</td>\n",
       "      <td>0.049345</td>\n",
       "      <td>0.047613</td>\n",
       "      <td>0.026147</td>\n",
       "      <td>0.021785</td>\n",
       "      <td>0.029247</td>\n",
       "      <td>0.021379</td>\n",
       "      <td>0.022850</td>\n",
       "      <td>0.019478</td>\n",
       "      <td>0.013890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_0</th>\n",
       "      <td>-0.030575</td>\n",
       "      <td>-0.271214</td>\n",
       "      <td>-0.057643</td>\n",
       "      <td>0.105364</td>\n",
       "      <td>0.019917</td>\n",
       "      <td>-0.039447</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.672164</td>\n",
       "      <td>0.574245</td>\n",
       "      <td>0.538841</td>\n",
       "      <td>...</td>\n",
       "      <td>0.179125</td>\n",
       "      <td>0.180635</td>\n",
       "      <td>0.176980</td>\n",
       "      <td>-0.079269</td>\n",
       "      <td>-0.070101</td>\n",
       "      <td>-0.070561</td>\n",
       "      <td>-0.064005</td>\n",
       "      <td>-0.058190</td>\n",
       "      <td>-0.058673</td>\n",
       "      <td>0.324794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_2</th>\n",
       "      <td>-0.011215</td>\n",
       "      <td>-0.296382</td>\n",
       "      <td>-0.070771</td>\n",
       "      <td>0.121566</td>\n",
       "      <td>0.024199</td>\n",
       "      <td>-0.050148</td>\n",
       "      <td>0.672164</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.766552</td>\n",
       "      <td>0.662067</td>\n",
       "      <td>...</td>\n",
       "      <td>0.222237</td>\n",
       "      <td>0.221348</td>\n",
       "      <td>0.219403</td>\n",
       "      <td>-0.080701</td>\n",
       "      <td>-0.058990</td>\n",
       "      <td>-0.055901</td>\n",
       "      <td>-0.046858</td>\n",
       "      <td>-0.037093</td>\n",
       "      <td>-0.036500</td>\n",
       "      <td>0.263551</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_3</th>\n",
       "      <td>-0.018494</td>\n",
       "      <td>-0.286123</td>\n",
       "      <td>-0.066096</td>\n",
       "      <td>0.114025</td>\n",
       "      <td>0.032688</td>\n",
       "      <td>-0.053048</td>\n",
       "      <td>0.574245</td>\n",
       "      <td>0.766552</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.777359</td>\n",
       "      <td>...</td>\n",
       "      <td>0.227202</td>\n",
       "      <td>0.225145</td>\n",
       "      <td>0.222327</td>\n",
       "      <td>0.001295</td>\n",
       "      <td>-0.066793</td>\n",
       "      <td>-0.053311</td>\n",
       "      <td>-0.046067</td>\n",
       "      <td>-0.035863</td>\n",
       "      <td>-0.035861</td>\n",
       "      <td>0.235253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_4</th>\n",
       "      <td>-0.002735</td>\n",
       "      <td>-0.267460</td>\n",
       "      <td>-0.060173</td>\n",
       "      <td>0.108793</td>\n",
       "      <td>0.033122</td>\n",
       "      <td>-0.049722</td>\n",
       "      <td>0.538841</td>\n",
       "      <td>0.662067</td>\n",
       "      <td>0.777359</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.245917</td>\n",
       "      <td>0.242902</td>\n",
       "      <td>0.239154</td>\n",
       "      <td>-0.009362</td>\n",
       "      <td>-0.001944</td>\n",
       "      <td>-0.069235</td>\n",
       "      <td>-0.043461</td>\n",
       "      <td>-0.033590</td>\n",
       "      <td>-0.026565</td>\n",
       "      <td>0.216614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_5</th>\n",
       "      <td>-0.022199</td>\n",
       "      <td>-0.249411</td>\n",
       "      <td>-0.055064</td>\n",
       "      <td>0.097520</td>\n",
       "      <td>0.035629</td>\n",
       "      <td>-0.053826</td>\n",
       "      <td>0.509426</td>\n",
       "      <td>0.622780</td>\n",
       "      <td>0.686775</td>\n",
       "      <td>0.819835</td>\n",
       "      <td>...</td>\n",
       "      <td>0.271915</td>\n",
       "      <td>0.269783</td>\n",
       "      <td>0.262509</td>\n",
       "      <td>-0.006089</td>\n",
       "      <td>-0.003191</td>\n",
       "      <td>0.009062</td>\n",
       "      <td>-0.058299</td>\n",
       "      <td>-0.033337</td>\n",
       "      <td>-0.023027</td>\n",
       "      <td>0.204149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_6</th>\n",
       "      <td>-0.020270</td>\n",
       "      <td>-0.235195</td>\n",
       "      <td>-0.044008</td>\n",
       "      <td>0.082316</td>\n",
       "      <td>0.034345</td>\n",
       "      <td>-0.048773</td>\n",
       "      <td>0.474553</td>\n",
       "      <td>0.575501</td>\n",
       "      <td>0.632684</td>\n",
       "      <td>0.716449</td>\n",
       "      <td>...</td>\n",
       "      <td>0.266356</td>\n",
       "      <td>0.290894</td>\n",
       "      <td>0.285091</td>\n",
       "      <td>-0.001496</td>\n",
       "      <td>-0.005223</td>\n",
       "      <td>0.005834</td>\n",
       "      <td>0.019018</td>\n",
       "      <td>-0.046434</td>\n",
       "      <td>-0.025299</td>\n",
       "      <td>0.186866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILL_AMT1</th>\n",
       "      <td>0.019389</td>\n",
       "      <td>0.285430</td>\n",
       "      <td>-0.033642</td>\n",
       "      <td>0.023581</td>\n",
       "      <td>-0.023472</td>\n",
       "      <td>0.056239</td>\n",
       "      <td>0.187068</td>\n",
       "      <td>0.234887</td>\n",
       "      <td>0.208473</td>\n",
       "      <td>0.202812</td>\n",
       "      <td>...</td>\n",
       "      <td>0.860272</td>\n",
       "      <td>0.829779</td>\n",
       "      <td>0.802650</td>\n",
       "      <td>0.140277</td>\n",
       "      <td>0.099355</td>\n",
       "      <td>0.156887</td>\n",
       "      <td>0.158303</td>\n",
       "      <td>0.167026</td>\n",
       "      <td>0.179341</td>\n",
       "      <td>-0.019644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILL_AMT2</th>\n",
       "      <td>0.017982</td>\n",
       "      <td>0.278314</td>\n",
       "      <td>-0.031183</td>\n",
       "      <td>0.018749</td>\n",
       "      <td>-0.021602</td>\n",
       "      <td>0.054283</td>\n",
       "      <td>0.189859</td>\n",
       "      <td>0.235257</td>\n",
       "      <td>0.237295</td>\n",
       "      <td>0.225816</td>\n",
       "      <td>...</td>\n",
       "      <td>0.892482</td>\n",
       "      <td>0.859778</td>\n",
       "      <td>0.831594</td>\n",
       "      <td>0.280365</td>\n",
       "      <td>0.100851</td>\n",
       "      <td>0.150718</td>\n",
       "      <td>0.147398</td>\n",
       "      <td>0.157957</td>\n",
       "      <td>0.174256</td>\n",
       "      <td>-0.014193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILL_AMT3</th>\n",
       "      <td>0.024354</td>\n",
       "      <td>0.283236</td>\n",
       "      <td>-0.024563</td>\n",
       "      <td>0.013002</td>\n",
       "      <td>-0.024909</td>\n",
       "      <td>0.053710</td>\n",
       "      <td>0.179785</td>\n",
       "      <td>0.224146</td>\n",
       "      <td>0.227494</td>\n",
       "      <td>0.244983</td>\n",
       "      <td>...</td>\n",
       "      <td>0.923969</td>\n",
       "      <td>0.883910</td>\n",
       "      <td>0.853320</td>\n",
       "      <td>0.244335</td>\n",
       "      <td>0.316936</td>\n",
       "      <td>0.130011</td>\n",
       "      <td>0.143405</td>\n",
       "      <td>0.179712</td>\n",
       "      <td>0.182326</td>\n",
       "      <td>-0.014076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILL_AMT4</th>\n",
       "      <td>0.040351</td>\n",
       "      <td>0.293988</td>\n",
       "      <td>-0.021880</td>\n",
       "      <td>-0.000451</td>\n",
       "      <td>-0.023344</td>\n",
       "      <td>0.051353</td>\n",
       "      <td>0.179125</td>\n",
       "      <td>0.222237</td>\n",
       "      <td>0.227202</td>\n",
       "      <td>0.245917</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.940134</td>\n",
       "      <td>0.900941</td>\n",
       "      <td>0.233012</td>\n",
       "      <td>0.207564</td>\n",
       "      <td>0.300023</td>\n",
       "      <td>0.130191</td>\n",
       "      <td>0.160433</td>\n",
       "      <td>0.177637</td>\n",
       "      <td>-0.010156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILL_AMT5</th>\n",
       "      <td>0.016705</td>\n",
       "      <td>0.295562</td>\n",
       "      <td>-0.017005</td>\n",
       "      <td>-0.007567</td>\n",
       "      <td>-0.025393</td>\n",
       "      <td>0.049345</td>\n",
       "      <td>0.180635</td>\n",
       "      <td>0.221348</td>\n",
       "      <td>0.225145</td>\n",
       "      <td>0.242902</td>\n",
       "      <td>...</td>\n",
       "      <td>0.940134</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.946197</td>\n",
       "      <td>0.217031</td>\n",
       "      <td>0.181246</td>\n",
       "      <td>0.252305</td>\n",
       "      <td>0.293118</td>\n",
       "      <td>0.141574</td>\n",
       "      <td>0.164184</td>\n",
       "      <td>-0.006760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILL_AMT6</th>\n",
       "      <td>0.016730</td>\n",
       "      <td>0.290389</td>\n",
       "      <td>-0.016733</td>\n",
       "      <td>-0.009099</td>\n",
       "      <td>-0.021207</td>\n",
       "      <td>0.047613</td>\n",
       "      <td>0.176980</td>\n",
       "      <td>0.219403</td>\n",
       "      <td>0.222327</td>\n",
       "      <td>0.239154</td>\n",
       "      <td>...</td>\n",
       "      <td>0.900941</td>\n",
       "      <td>0.946197</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.199965</td>\n",
       "      <td>0.172663</td>\n",
       "      <td>0.233770</td>\n",
       "      <td>0.250237</td>\n",
       "      <td>0.307729</td>\n",
       "      <td>0.115494</td>\n",
       "      <td>-0.005372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_AMT1</th>\n",
       "      <td>0.009742</td>\n",
       "      <td>0.195236</td>\n",
       "      <td>-0.000242</td>\n",
       "      <td>-0.037456</td>\n",
       "      <td>-0.005979</td>\n",
       "      <td>0.026147</td>\n",
       "      <td>-0.079269</td>\n",
       "      <td>-0.080701</td>\n",
       "      <td>0.001295</td>\n",
       "      <td>-0.009362</td>\n",
       "      <td>...</td>\n",
       "      <td>0.233012</td>\n",
       "      <td>0.217031</td>\n",
       "      <td>0.199965</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.285576</td>\n",
       "      <td>0.252191</td>\n",
       "      <td>0.199558</td>\n",
       "      <td>0.148459</td>\n",
       "      <td>0.185735</td>\n",
       "      <td>-0.072929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_AMT2</th>\n",
       "      <td>0.008406</td>\n",
       "      <td>0.178408</td>\n",
       "      <td>-0.001391</td>\n",
       "      <td>-0.030038</td>\n",
       "      <td>-0.008093</td>\n",
       "      <td>0.021785</td>\n",
       "      <td>-0.070101</td>\n",
       "      <td>-0.058990</td>\n",
       "      <td>-0.066793</td>\n",
       "      <td>-0.001944</td>\n",
       "      <td>...</td>\n",
       "      <td>0.207564</td>\n",
       "      <td>0.181246</td>\n",
       "      <td>0.172663</td>\n",
       "      <td>0.285576</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.244770</td>\n",
       "      <td>0.180107</td>\n",
       "      <td>0.180908</td>\n",
       "      <td>0.157634</td>\n",
       "      <td>-0.058579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_AMT3</th>\n",
       "      <td>0.039151</td>\n",
       "      <td>0.210167</td>\n",
       "      <td>-0.008597</td>\n",
       "      <td>-0.039943</td>\n",
       "      <td>-0.003541</td>\n",
       "      <td>0.029247</td>\n",
       "      <td>-0.070561</td>\n",
       "      <td>-0.055901</td>\n",
       "      <td>-0.053311</td>\n",
       "      <td>-0.069235</td>\n",
       "      <td>...</td>\n",
       "      <td>0.300023</td>\n",
       "      <td>0.252305</td>\n",
       "      <td>0.233770</td>\n",
       "      <td>0.252191</td>\n",
       "      <td>0.244770</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.216325</td>\n",
       "      <td>0.159214</td>\n",
       "      <td>0.162740</td>\n",
       "      <td>-0.056250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_AMT4</th>\n",
       "      <td>0.007793</td>\n",
       "      <td>0.203242</td>\n",
       "      <td>-0.002229</td>\n",
       "      <td>-0.038218</td>\n",
       "      <td>-0.012659</td>\n",
       "      <td>0.021379</td>\n",
       "      <td>-0.064005</td>\n",
       "      <td>-0.046858</td>\n",
       "      <td>-0.046067</td>\n",
       "      <td>-0.043461</td>\n",
       "      <td>...</td>\n",
       "      <td>0.130191</td>\n",
       "      <td>0.293118</td>\n",
       "      <td>0.250237</td>\n",
       "      <td>0.199558</td>\n",
       "      <td>0.180107</td>\n",
       "      <td>0.216325</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.151830</td>\n",
       "      <td>0.157834</td>\n",
       "      <td>-0.056827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_AMT5</th>\n",
       "      <td>0.000652</td>\n",
       "      <td>0.217202</td>\n",
       "      <td>-0.001667</td>\n",
       "      <td>-0.040358</td>\n",
       "      <td>-0.001205</td>\n",
       "      <td>0.022850</td>\n",
       "      <td>-0.058190</td>\n",
       "      <td>-0.037093</td>\n",
       "      <td>-0.035863</td>\n",
       "      <td>-0.033590</td>\n",
       "      <td>...</td>\n",
       "      <td>0.160433</td>\n",
       "      <td>0.141574</td>\n",
       "      <td>0.307729</td>\n",
       "      <td>0.148459</td>\n",
       "      <td>0.180908</td>\n",
       "      <td>0.159214</td>\n",
       "      <td>0.151830</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.154896</td>\n",
       "      <td>-0.055124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_AMT6</th>\n",
       "      <td>0.003000</td>\n",
       "      <td>0.219595</td>\n",
       "      <td>-0.002766</td>\n",
       "      <td>-0.037200</td>\n",
       "      <td>-0.006641</td>\n",
       "      <td>0.019478</td>\n",
       "      <td>-0.058673</td>\n",
       "      <td>-0.036500</td>\n",
       "      <td>-0.035861</td>\n",
       "      <td>-0.026565</td>\n",
       "      <td>...</td>\n",
       "      <td>0.177637</td>\n",
       "      <td>0.164184</td>\n",
       "      <td>0.115494</td>\n",
       "      <td>0.185735</td>\n",
       "      <td>0.157634</td>\n",
       "      <td>0.162740</td>\n",
       "      <td>0.157834</td>\n",
       "      <td>0.154896</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.053183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>default.payment.next.month</th>\n",
       "      <td>-0.013952</td>\n",
       "      <td>-0.153520</td>\n",
       "      <td>-0.039961</td>\n",
       "      <td>0.028006</td>\n",
       "      <td>-0.024339</td>\n",
       "      <td>0.013890</td>\n",
       "      <td>0.324794</td>\n",
       "      <td>0.263551</td>\n",
       "      <td>0.235253</td>\n",
       "      <td>0.216614</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.010156</td>\n",
       "      <td>-0.006760</td>\n",
       "      <td>-0.005372</td>\n",
       "      <td>-0.072929</td>\n",
       "      <td>-0.058579</td>\n",
       "      <td>-0.056250</td>\n",
       "      <td>-0.056827</td>\n",
       "      <td>-0.055124</td>\n",
       "      <td>-0.053183</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  ID  LIMIT_BAL       SEX  EDUCATION  \\\n",
       "ID                          1.000000   0.026179  0.018497   0.039177   \n",
       "LIMIT_BAL                   0.026179   1.000000  0.024755  -0.219161   \n",
       "SEX                         0.018497   0.024755  1.000000   0.014232   \n",
       "EDUCATION                   0.039177  -0.219161  0.014232   1.000000   \n",
       "MARRIAGE                   -0.029079  -0.108139 -0.031389  -0.143464   \n",
       "AGE                         0.018678   0.144713 -0.090874   0.175061   \n",
       "PAY_0                      -0.030575  -0.271214 -0.057643   0.105364   \n",
       "PAY_2                      -0.011215  -0.296382 -0.070771   0.121566   \n",
       "PAY_3                      -0.018494  -0.286123 -0.066096   0.114025   \n",
       "PAY_4                      -0.002735  -0.267460 -0.060173   0.108793   \n",
       "PAY_5                      -0.022199  -0.249411 -0.055064   0.097520   \n",
       "PAY_6                      -0.020270  -0.235195 -0.044008   0.082316   \n",
       "BILL_AMT1                   0.019389   0.285430 -0.033642   0.023581   \n",
       "BILL_AMT2                   0.017982   0.278314 -0.031183   0.018749   \n",
       "BILL_AMT3                   0.024354   0.283236 -0.024563   0.013002   \n",
       "BILL_AMT4                   0.040351   0.293988 -0.021880  -0.000451   \n",
       "BILL_AMT5                   0.016705   0.295562 -0.017005  -0.007567   \n",
       "BILL_AMT6                   0.016730   0.290389 -0.016733  -0.009099   \n",
       "PAY_AMT1                    0.009742   0.195236 -0.000242  -0.037456   \n",
       "PAY_AMT2                    0.008406   0.178408 -0.001391  -0.030038   \n",
       "PAY_AMT3                    0.039151   0.210167 -0.008597  -0.039943   \n",
       "PAY_AMT4                    0.007793   0.203242 -0.002229  -0.038218   \n",
       "PAY_AMT5                    0.000652   0.217202 -0.001667  -0.040358   \n",
       "PAY_AMT6                    0.003000   0.219595 -0.002766  -0.037200   \n",
       "default.payment.next.month -0.013952  -0.153520 -0.039961   0.028006   \n",
       "\n",
       "                            MARRIAGE       AGE     PAY_0     PAY_2     PAY_3  \\\n",
       "ID                         -0.029079  0.018678 -0.030575 -0.011215 -0.018494   \n",
       "LIMIT_BAL                  -0.108139  0.144713 -0.271214 -0.296382 -0.286123   \n",
       "SEX                        -0.031389 -0.090874 -0.057643 -0.070771 -0.066096   \n",
       "EDUCATION                  -0.143464  0.175061  0.105364  0.121566  0.114025   \n",
       "MARRIAGE                    1.000000 -0.414170  0.019917  0.024199  0.032688   \n",
       "AGE                        -0.414170  1.000000 -0.039447 -0.050148 -0.053048   \n",
       "PAY_0                       0.019917 -0.039447  1.000000  0.672164  0.574245   \n",
       "PAY_2                       0.024199 -0.050148  0.672164  1.000000  0.766552   \n",
       "PAY_3                       0.032688 -0.053048  0.574245  0.766552  1.000000   \n",
       "PAY_4                       0.033122 -0.049722  0.538841  0.662067  0.777359   \n",
       "PAY_5                       0.035629 -0.053826  0.509426  0.622780  0.686775   \n",
       "PAY_6                       0.034345 -0.048773  0.474553  0.575501  0.632684   \n",
       "BILL_AMT1                  -0.023472  0.056239  0.187068  0.234887  0.208473   \n",
       "BILL_AMT2                  -0.021602  0.054283  0.189859  0.235257  0.237295   \n",
       "BILL_AMT3                  -0.024909  0.053710  0.179785  0.224146  0.227494   \n",
       "BILL_AMT4                  -0.023344  0.051353  0.179125  0.222237  0.227202   \n",
       "BILL_AMT5                  -0.025393  0.049345  0.180635  0.221348  0.225145   \n",
       "BILL_AMT6                  -0.021207  0.047613  0.176980  0.219403  0.222327   \n",
       "PAY_AMT1                   -0.005979  0.026147 -0.079269 -0.080701  0.001295   \n",
       "PAY_AMT2                   -0.008093  0.021785 -0.070101 -0.058990 -0.066793   \n",
       "PAY_AMT3                   -0.003541  0.029247 -0.070561 -0.055901 -0.053311   \n",
       "PAY_AMT4                   -0.012659  0.021379 -0.064005 -0.046858 -0.046067   \n",
       "PAY_AMT5                   -0.001205  0.022850 -0.058190 -0.037093 -0.035863   \n",
       "PAY_AMT6                   -0.006641  0.019478 -0.058673 -0.036500 -0.035861   \n",
       "default.payment.next.month -0.024339  0.013890  0.324794  0.263551  0.235253   \n",
       "\n",
       "                               PAY_4             ...              BILL_AMT4  \\\n",
       "ID                         -0.002735             ...               0.040351   \n",
       "LIMIT_BAL                  -0.267460             ...               0.293988   \n",
       "SEX                        -0.060173             ...              -0.021880   \n",
       "EDUCATION                   0.108793             ...              -0.000451   \n",
       "MARRIAGE                    0.033122             ...              -0.023344   \n",
       "AGE                        -0.049722             ...               0.051353   \n",
       "PAY_0                       0.538841             ...               0.179125   \n",
       "PAY_2                       0.662067             ...               0.222237   \n",
       "PAY_3                       0.777359             ...               0.227202   \n",
       "PAY_4                       1.000000             ...               0.245917   \n",
       "PAY_5                       0.819835             ...               0.271915   \n",
       "PAY_6                       0.716449             ...               0.266356   \n",
       "BILL_AMT1                   0.202812             ...               0.860272   \n",
       "BILL_AMT2                   0.225816             ...               0.892482   \n",
       "BILL_AMT3                   0.244983             ...               0.923969   \n",
       "BILL_AMT4                   0.245917             ...               1.000000   \n",
       "BILL_AMT5                   0.242902             ...               0.940134   \n",
       "BILL_AMT6                   0.239154             ...               0.900941   \n",
       "PAY_AMT1                   -0.009362             ...               0.233012   \n",
       "PAY_AMT2                   -0.001944             ...               0.207564   \n",
       "PAY_AMT3                   -0.069235             ...               0.300023   \n",
       "PAY_AMT4                   -0.043461             ...               0.130191   \n",
       "PAY_AMT5                   -0.033590             ...               0.160433   \n",
       "PAY_AMT6                   -0.026565             ...               0.177637   \n",
       "default.payment.next.month  0.216614             ...              -0.010156   \n",
       "\n",
       "                            BILL_AMT5  BILL_AMT6  PAY_AMT1  PAY_AMT2  \\\n",
       "ID                           0.016705   0.016730  0.009742  0.008406   \n",
       "LIMIT_BAL                    0.295562   0.290389  0.195236  0.178408   \n",
       "SEX                         -0.017005  -0.016733 -0.000242 -0.001391   \n",
       "EDUCATION                   -0.007567  -0.009099 -0.037456 -0.030038   \n",
       "MARRIAGE                    -0.025393  -0.021207 -0.005979 -0.008093   \n",
       "AGE                          0.049345   0.047613  0.026147  0.021785   \n",
       "PAY_0                        0.180635   0.176980 -0.079269 -0.070101   \n",
       "PAY_2                        0.221348   0.219403 -0.080701 -0.058990   \n",
       "PAY_3                        0.225145   0.222327  0.001295 -0.066793   \n",
       "PAY_4                        0.242902   0.239154 -0.009362 -0.001944   \n",
       "PAY_5                        0.269783   0.262509 -0.006089 -0.003191   \n",
       "PAY_6                        0.290894   0.285091 -0.001496 -0.005223   \n",
       "BILL_AMT1                    0.829779   0.802650  0.140277  0.099355   \n",
       "BILL_AMT2                    0.859778   0.831594  0.280365  0.100851   \n",
       "BILL_AMT3                    0.883910   0.853320  0.244335  0.316936   \n",
       "BILL_AMT4                    0.940134   0.900941  0.233012  0.207564   \n",
       "BILL_AMT5                    1.000000   0.946197  0.217031  0.181246   \n",
       "BILL_AMT6                    0.946197   1.000000  0.199965  0.172663   \n",
       "PAY_AMT1                     0.217031   0.199965  1.000000  0.285576   \n",
       "PAY_AMT2                     0.181246   0.172663  0.285576  1.000000   \n",
       "PAY_AMT3                     0.252305   0.233770  0.252191  0.244770   \n",
       "PAY_AMT4                     0.293118   0.250237  0.199558  0.180107   \n",
       "PAY_AMT5                     0.141574   0.307729  0.148459  0.180908   \n",
       "PAY_AMT6                     0.164184   0.115494  0.185735  0.157634   \n",
       "default.payment.next.month  -0.006760  -0.005372 -0.072929 -0.058579   \n",
       "\n",
       "                            PAY_AMT3  PAY_AMT4  PAY_AMT5  PAY_AMT6  \\\n",
       "ID                          0.039151  0.007793  0.000652  0.003000   \n",
       "LIMIT_BAL                   0.210167  0.203242  0.217202  0.219595   \n",
       "SEX                        -0.008597 -0.002229 -0.001667 -0.002766   \n",
       "EDUCATION                  -0.039943 -0.038218 -0.040358 -0.037200   \n",
       "MARRIAGE                   -0.003541 -0.012659 -0.001205 -0.006641   \n",
       "AGE                         0.029247  0.021379  0.022850  0.019478   \n",
       "PAY_0                      -0.070561 -0.064005 -0.058190 -0.058673   \n",
       "PAY_2                      -0.055901 -0.046858 -0.037093 -0.036500   \n",
       "PAY_3                      -0.053311 -0.046067 -0.035863 -0.035861   \n",
       "PAY_4                      -0.069235 -0.043461 -0.033590 -0.026565   \n",
       "PAY_5                       0.009062 -0.058299 -0.033337 -0.023027   \n",
       "PAY_6                       0.005834  0.019018 -0.046434 -0.025299   \n",
       "BILL_AMT1                   0.156887  0.158303  0.167026  0.179341   \n",
       "BILL_AMT2                   0.150718  0.147398  0.157957  0.174256   \n",
       "BILL_AMT3                   0.130011  0.143405  0.179712  0.182326   \n",
       "BILL_AMT4                   0.300023  0.130191  0.160433  0.177637   \n",
       "BILL_AMT5                   0.252305  0.293118  0.141574  0.164184   \n",
       "BILL_AMT6                   0.233770  0.250237  0.307729  0.115494   \n",
       "PAY_AMT1                    0.252191  0.199558  0.148459  0.185735   \n",
       "PAY_AMT2                    0.244770  0.180107  0.180908  0.157634   \n",
       "PAY_AMT3                    1.000000  0.216325  0.159214  0.162740   \n",
       "PAY_AMT4                    0.216325  1.000000  0.151830  0.157834   \n",
       "PAY_AMT5                    0.159214  0.151830  1.000000  0.154896   \n",
       "PAY_AMT6                    0.162740  0.157834  0.154896  1.000000   \n",
       "default.payment.next.month -0.056250 -0.056827 -0.055124 -0.053183   \n",
       "\n",
       "                            default.payment.next.month  \n",
       "ID                                           -0.013952  \n",
       "LIMIT_BAL                                    -0.153520  \n",
       "SEX                                          -0.039961  \n",
       "EDUCATION                                     0.028006  \n",
       "MARRIAGE                                     -0.024339  \n",
       "AGE                                           0.013890  \n",
       "PAY_0                                         0.324794  \n",
       "PAY_2                                         0.263551  \n",
       "PAY_3                                         0.235253  \n",
       "PAY_4                                         0.216614  \n",
       "PAY_5                                         0.204149  \n",
       "PAY_6                                         0.186866  \n",
       "BILL_AMT1                                    -0.019644  \n",
       "BILL_AMT2                                    -0.014193  \n",
       "BILL_AMT3                                    -0.014076  \n",
       "BILL_AMT4                                    -0.010156  \n",
       "BILL_AMT5                                    -0.006760  \n",
       "BILL_AMT6                                    -0.005372  \n",
       "PAY_AMT1                                     -0.072929  \n",
       "PAY_AMT2                                     -0.058579  \n",
       "PAY_AMT3                                     -0.056250  \n",
       "PAY_AMT4                                     -0.056827  \n",
       "PAY_AMT5                                     -0.055124  \n",
       "PAY_AMT6                                     -0.053183  \n",
       "default.payment.next.month                    1.000000  \n",
       "\n",
       "[25 rows x 25 columns]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr.transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "mask=np.zeros_like(corr,dtype=np.bool)\n",
    "mask[np.triu_indices_from(mask)]=True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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l7jFjxgyTvj9ERJZAppAZ/JAyLg0YgYeHB4KDg1G/fn106tRJt/3rr79GcnIyxo4di5yc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\nREQGjI0AERGRAft/VQuWxxtFl1sAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1e1bbf79780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with sb.axes_style(\"white\"):\n",
    "    a=sb.heatmap(corr,mask=mask,vmax=0.7,square=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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AABIQbwAAAAmINwAAgATEGwAAQALiDQAAIAHxBgAAkIB4AwAASEC8AQAAJCDeAAAAEhBv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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1e1b8d1ea58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, a1=matplotlib.pyplot.subplots(figsize=(15,9))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "customap=sb.diverging_palette(220,10,as_cmap=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1e1bfa3cc50>"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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kjCETEZUazMYnozNkNr5KpcLixYsxceJEDB8+HOnp6fDy8jL0kImIShcFf2bP\nM3sZKols/C5duqBLly7FGygRUVnCaXySI2bjExEZkIzO1KViNj4REZEIGdfER4C/YNHEwQgjkY5n\n9iSa1Gz8n6/cEl3v3KwRHqami66vZmOFzNt/iqo1b1APgPRsfLHjqWZjBQBI8g8WVV9j7nQAQOLk\n2aLq664IBAD8OXKCqPp6G1YDAG71HyqqvlF0zlc45ZSlL7esddYrq95oOI1PRERUyjFBjwypJLLx\nExIS8N5778HHxwcjR45ESkqK4Q+EiKgUUalUkh9ywTN7mTJ2Nv78+fMxffp0tGrVCgcOHMDt27dR\nqVKlkjo8IiLl4Zk9GZOhs/GfPXuG5ORk/PTTT1Cr1YiPj0eLFi1K6nCIiJRJwd+zZ7OXKWNm4z95\n8gTXr19Hp06d8O233+LJkye5vsNPRET/oeBmz2l8mTJmNr6trS2sra3RsWNHAED37t0RExODwYMH\nG+FIiIhKBxWvxqeSYKhsfEtLSzRo0ABnz55Fu3btcObMGb0YXiIiygOz8cnYDJmNDwD+/v5YunQp\nvLy88OjRI3h6ehpyuEREpQ+n8cmQSiIbv2nTpnqf+RMRUSE4jU9yxGx8IiLDUfItbpmNT0REJILY\nyO2XvYjfftV4Zk+iSc3GfxK9T3S9bf8+SE57Jrq+cnlL0eOpUCEnK1tqfda9v0TVm9WuCQDQnDor\nqt66Y7uc8Rw+Km48PXK+XZH6ywlR9TZd38oZz/FT4sbTpWORti+1ntn4rC+pemNJt7SQvI4Rk/ol\nUe6cBBEREYnCZl8ML2fYDx8+HF5eXrh8+TJWrlwpXPzWuXPnXOu9/LxYfn5+GDhwoN4ytVqNd955\nR2/ZwYMH0aRJEyQmJmLGjBlQq9VwcXFBr169oFarsWjRIqH2/PnzUKvVksZBRESGodVqsWDBAnh7\ne0OtViMhIUHv+SNHjmDQoEHw9vbG9u3bi7UvTuMX08vhN8ePH8fy5cvRvHlzg+4jPT0dcXFxcHR0\nRGxsbK4r9a9cuYJmzZoBAPbu3Ys6deoAAJYuXQog581F1apVMXTov7c8XbduHaKjo2FlZWXQsRIR\nkTg//vgjMjMzsW3bNsTHxyMgIAAhISEAgKysLCxZsgQ7duyAlZUVhg4dChcXF1StWrRrAHhmb0BP\nnz4tMKa2qPbv349OnTrh3XffxebNm/We69u3L/bs2SPsPyMjQ9QvQ7169bBy5UqDj5WIiMSJi4tD\n165dAQDZgBG0AAAgAElEQVStWrXCxYsXhedu3ryJevXqwdbWFubm5mjbti3OnDlT5H2x2RfTiwx7\nb29vzJkzB3379jX4Pl7cze6tt97C5cuXkZSUJDzn4uKCY8eOQafT4cCBA+jdu7eobfbq1QvlynFi\nh4joVXlx59IXTE1NkZ2dLTz34mJhALC2tkZqamqR98VmX0wdO3ZEWFgYtm3bhl27dmH69Ol49kz8\nVeWFuXnzJq5fv46AgACMGTMGKpVK7/N+CwsLNGvWDOfOncOPP/4IV1dXg+2biIiMx8bGBhqNRvhZ\nq9UKJ2H/fU6j0eg1f6nY7A2oqJ+lFCQyMhLTpk1DaGgoQkNDsWnTJkRFRSEzM1Oo6devHzZu3IiK\nFSvC2tra4GMgIiLDa9OmDY4dOwYAiI+Ph6Ojo/Bc48aNkZCQgMePHyMzMxNnz55F69ati7wvzuMW\n04tpfBMTE2g0Gvj6+uLu3bvC848fP4aHh4fw86hRowAAa9euRWRkJICc6ZmwsLBc287MzMSePXsQ\nHR0tLKtduzaaNm2KAwcOCMveeust+Pr6YsmSJQY/PiIiMg5XV1fExMRgyJAh0Ol08Pf3x/fff4+0\ntDR4e3vD19cXo0ePhk6nw6BBg1CjRo0i74vNvhg6dOiQK5v+vy5dupTn8kmTJhW6fXNzcxw/fjzX\n8nXr1gEA3N3dhWUnTvwbcPLfr2jkt6+6desW++scRERUNCYmJvj000/1ljVu3Fj4s4uLC1xcXAyy\nL8blysTEiRPx5MkTvWU2NjbC1zCIiOjVkpIi+kJxPmc3JDZ7IiIiEaREer9QubylEUYiHafxSTTJ\n2fjf/yC63ta9t+Ttyy4b/+RpUfXWndrnjEdiNr7kLP0jx0TV27i8XSL117v0ElX/2vEDsstaZ72y\n6o1FyafGbPZEREQiaBXc7dnsiyE2NhZTp06Fg4MDdDodMjMz4efnh8OHDwvxtJ07d0ZMTIzeennF\n1xbGz88P8fHx2L17t7BMrVbj0aNH2L9/v7Ds4MGDmDRpEg4fPoxly5bhwYMHuHv3LszMzFC9enU4\nOjrC19cXc+fOxd27d5GZmYnx48ejR48exX9BiIhKMSV/6s1mX0xKzMaPioqCnZ0dgoKC8PjxYwwc\nOJDNnoioEEpu9gzVMSClZOP37t0bU6ZMAZDzy2tqamrwMRMRlTZanU7yQy7Y7ItJidn41tbWsLGx\nQWpqKiZPnoypU6cafMxERKWNTif9IRds9sWk1Gz8+/fvY8SIERgwYIBeOA8REeVNp9NJfsgFP7M3\nIGNm4/v4+AAA7t27B29vb0yYMEGokZqN/+jRI4waNQoLFixAp06dDD5mIqLSSAv5NG+p2OyLSYnZ\n+GvWrMHTp0+xevVqrF69GkBOBK+lpTzCH4iI5EhOZ+pSsdkXg1Kz8efNm4d58+YVun8iIvqXnC64\nk4pxuTLBbHwiInm7/fdjyes0qGJnhJFIx2ZPREQkwq2HKZLXaVStkhFGIh2n8Uk0ydn40ftE19v2\n76P4bPy003Gi6su3bwsASP0590c0ebFx7pJTLzGL/p+DR0TVV3DLuYXmP4d+Elfv2r1I9VKy8cXW\nvqiXWzY7619tvbEo+dSYzZ6IiEgEJU+Es9kXg1Kz8efOnYt58+bhjz/+gEqlwsKFC+Ho6Fj8F4SI\nqBTjV+/KMCVm4//4448AgK1btyI2NhbLli3jhYBERIVQ8pk9E/QMSCnZ+D179sSiRYsA5IT0VKxY\n0eBjJiIqbZScoMdmX0xKzMYHgHLlymH27NlYtGgR43KJiETQ6qQ/5ILNvpiUmo0PAIGBgThw4ADm\nz5+PtLQ0g42ZiKg0UvKZPT+zNyClZOPv3r0bSUlJ+OCDD2BlZQWVSgUTE77vIyIqiJyat1Rs9sWk\nxGx8Nzc3zJkzBz4+PsjOzsbcuXOZi09EVAglx+Wy2ReDUrPxy5cvj+XLlxe6fyIi+peSmz3jcmWC\n2fhERPJ2LuGe5HVa169thJFIx2ZPREQkQtztu4UX/UfbBnWMMBLpOI1PomUnPRRdW65GNTzZ+b3o\nelsPd2bj56OksvGf7jlQSGWOiv1ycuuf7jsorr6PGwDjZuMzS5/1L9cbi5JPjdnsiYiIRFDyRDi/\nb1UMsbGx6NSpE9RqNYYPHw4vLy9cvnwZK1euFL4L37lz51zrvfy8WH5+fhg4cKDeMrVajXfeeUdv\n2cGDB9GkSRMkJiZixowZUKvVcHFxQa9evaBWq4XkPAD4+++/0a1bN9y8eVPSWIiIyiKtTif5IRc8\nsy8mJWbjA0BWVhYWLFjAr9wREYnEM3sCoJxsfCAnPW/IkCGoXr26wcdLRFQa6XTSH3LBZl9MSszG\n37lzJypXroyuXbsafKxERKWVkqfx2eyLSYnZ+FFRUThx4gTUajWuXLmC2bNn4+FD8VfaExGVRczG\nJwDKycZ/+aMAtVoNPz8/VKtWzeBjJyIieWCzLyYlZuMTEZF0cpqWl4rNvhiUmo3/srzeZBARUW5K\nbvaMy5UJZuMTEcnbT5elZ5J0f72xEUYiHZs9ERGRCEcu3ZC8jouTgxFGIh2n8Uk0qdn1is/G/yup\nkMocZjVrAJBhNv6hn0TVV3DtDkB6Nv6T3XtE1dsO7AdAXtn4zNIv3fXGolXwqTGbPRERkQhKnghn\nsy+G2NhYTJ06FQ4ODtDpdMjMzISfnx8OHz4sxNN27twZMTExeuvlFV9bGD8/P8THx2P37t3CMrVa\njUePHmH//v3CsoMHD2LSpEk4fPgwli1bhgcPHuDu3bswMzND9erV4ejoiPnz5+Pdd9+FjY0NAKBu\n3bq8kp+IqBBs9mWYErPxMzIyoNPpeCU+EZEEWii32TNBz4CUko1/9epVpKenY9SoURgxYgTi4+MN\nPmYiotJGyQl6bPbFpMRsfEtLS4wePRqhoaFYuHAhZs6ciezsbIOPm4ioNNHqpD+K4tmzZ5g0aRKG\nDRuGMWPGIDk5OVfN5s2bMWjQIAwePBj79u0rdJts9sWkxGz8hg0bon///lCpVGjYsCHs7OyYjU9E\nVAitVif5URRbtmyBo6MjIiIiMHDgQKxevVrv+eTkZGzZsgVbt27Fxo0bERgYWOgsApu9ARkzGz80\nNBShoaHYtGkToqKikJmZKdRIzcbfsWMHAgICAABJSUlITU1lNj4RUSFKaho/Li5OuCvp22+/nSup\ntXLlyti9ezfMzMzw6NEjWFhYQKVSFbhNXqBXTErMxh88eDDmzJmDoUOHQqVSwd/fH+XK8VeBiKgg\nxvgMPjIyEps2bdJbVqVKFSHvw9raOs+MkHLlyiE8PBwrV66EWq0udD/8P3wxKDUb39zcXLhSn4iI\nxDHG1fienp7w9PTUWzZx4kRoNBoAgEajQcWKFfNcd/jw4fDy8sKYMWNw6tQpdOzYMd/9MC5XJpiN\nT0QkbzvP/CZ5HY8335C8zvr166HRaDBp0iTs3bsXp0+fxsKFC4Xnb926heDgYKxcuRIAMHbsWIwZ\nMwbt27fPd5ts9kRERCJEnZbe7Ae1l97s09PTMXv2bDx8+BBmZmZYunQpqlWrhg0bNqBevXro0aMH\nVq1ahWPHjkGlUqFr166YOHFigdtksyfRJGfji8xOB3Ly05mNnzchG19iveRs/H0HRdVX7OMGAHgS\nXfjXfQDAtn8fAMrOxmeWvrLqjSUy9oLkdTw7tDDCSKTjZ/ZEREQiKPncmM2+GJScjf/111/jyJEj\nyMrKwtChQ3NdIEJERPrY7MswJWbjx8bG4ty5c9iyZQvS09Oxfv16g46XiKg00iq42TNUx4CUko1/\n/PhxODo64sMPP8S4cePg7Oxs8DETEZF8sNkXkxKz8VNSUnDx4kUsX75cyMZX8vQUEVFJ0Op0kh9y\nwWZfTErMxrezs0OXLl1gbm6ORo0awcLCIs8bLRAR0b941zsCoJxs/LZt2+KXX36BTqdDUlIS0tPT\nYWdnZ/CxExGVJiV11ztj4AV6xaTEbPzu3bvjzJkzGDx4MHQ6HRYsWABTU1NpB05EVMbI6UxdKjb7\nYlBqNj4AfPTRR4Xun4iI/qXkZs8EPZlgNj4Rkbyt//m05HVGOeefV1+SeGYvE6tWrXrVQyAiogIo\n+dSYzZ5Ek5pdr4mJFV1v3bmD5O0np4n71kPl8pYApGfjS62/myKuvk6lotUbe/zGrk//Le+PtP7L\n6g0nPPn+B1G1AGDr3hv/HDwiur6Cmwv+OXxUfH2Pbkg9GlN44f+z6dZZ8u++3LLllV5vLEqeCGez\nJyIiEkFO35uXil+9K6bY2Fh06tQJarUaarUaXl5eelfWDxgwQO8+xOHh4Rg9erTeNiZNmoSIiIgC\n95ORkYHOnTvjm2++EZYlJiaiSZMmWLt2rV7tuHHjoFarce3aNWFcb7zxBnx8fKBWq/Hzzz8Ltf7+\n/nrf2yciorzxe/Zl3ItgnbCwMISHh2PDhg14+vSpkGd/6tQppKamAgB8fHyg1WqFr93t3bsXWVlZ\nGDZsWIH7OHDgAPr06YNdu3ZBq9UKy+vVq6f3NbyUlBQkJCQAAJo0aSKMq1q1ali/fj3CwsLg7OyM\n5ORkvP/++zhyRPz0JxFRWcYEPRKkpqbCxMQEpqamiIyMRK9eveDq6ircrU6lUsHf3x8hISG4ceMG\n1qxZA39//0K3GxkZiUGDBqFp06Y4evTfzxsrVaqEKlWq4ObNmwBycvTFROZqNBpMmjQJAwYMKOKR\nEhGVLWz2ZdyLYJ0RI0Zg1qxZmD9/PnQ6HeLi4uDs7AwPDw+9qfJatWph8uTJ8Pb2xsyZMwu9ec7t\n27eRnp6Opk2bYtCgQXneDGfv3r0AgMOHD6Nnz56Fjtne3h4tW7YswtESEZVNSp7G5wV6BvDybW5f\niIiIgFarxQcffAAAePjwIU6ePIlOnToBAAYOHIigoCB069at0O1HRkYiPT1d+Kz/119/RUJCgpB6\n17NnT/j4+MDDwwPVqlWDpaWlIQ+PiIjAr95RHnbs2IE1a9bgtddeAwBER0dj8+bNQrMXKysrC/v2\n7cOuXbuE/PqQkBBERERArVYDyInbbdiwIYKCguDp6WnYAyEiIgC8Gp/+49KlS9DpdEKjB4BevXoh\nLi4O9+/fl7Stn376CU5OTno3qvHw8MB3332nd3c9d3d3xMXFSX4zQURE4nAavwzr0KEDOnTooLfM\nyckJu3bt0ltmYWGRK0c/JqbwoA43Nze4ubnpLatRowZOnToF4N8cfBcXF7i4uAAAGjdunOvGOvld\ndS8mo5+IiJQdqsNsfJm4cOECgoKCci1/5513Cv1aHhERGd/SPT9LXmdGP2eDj6MoeGYvEy1atMjz\nNrdERCQPSj4zZrMn0aRm16edjhNdX759W8nbl1v2+73HqaLqa9vZAACSnmpE1deoaA0AuP9E3PZr\n2eZsX26vT8bNP0TVWzRuiIzrN0XVAoDFa43xePuuwgv/n53Xu0j95UThhf/Pputbkn+X0878Kr7+\nzTZ4Er1PdL1t/z6yy6KXWz3lxmZPREQkAq/GL8OUmo1/5coVDBs2DGq1GqNHj8ajR4+K8zIQEZV6\nSr4an83eAJSYjf/ZZ59h/vz5CAsLg6urK9atW2fol4WIqFTRanWSH3LBZm9gSsnGDw4ORrNmzQAA\nz58/h4WFRVEOl4iozOCZfRmnxGz86tWrA8iJ3g0PD8d7770n8aiJiMoWJd8IhxfoGYBSs/H37duH\nkJAQrF27ttA3HEREZZ18Wrd0bPZGIvds/O+++w7btm1DWFiYXhQvERHlTU7T8lJxGt8I5J6N//z5\nc3z22WfCPe3VajVWrFghaVxERGUNp/HLMCVm45uamuL06dOF7puIiP6l5DN7ZuPLBLPxiYjkbf72\n/ZLXWeT1jhFGIh3P7GWC2fhERPKm5FNjNnsSLTvpoejacjWqSc4fl5qN/7fmWeGFAKpY53w7QW7Z\n+A/+SRNVX71C+SLVSx2PsV+f9F/Pi6q3atMS6fG/iaoFAKtWb+DZpaui6y2dmuJxVLToertB/fH0\nh8Oi6yv27oF/Dh8tvPD/VejRTfr2D+Z9y+o8t+/mIrvseqVm4yt5IpzNnoiISAQ5XXAnFa/GLyal\nZuPfuHEDQ4cOxZAhQ+Dr64vs7OzivAxERKWekq/GZ7M3ACVm4wcHB2P69OnYunUrgJyv+BERUf4Y\nl0sCpWTjr1y5Em+++SYyMzPx8OFD2NjYFPGIiYjKBjb7Mk6J2fimpqa4e/cu+vXrh5SUFDRt2rQI\nR05EVHZoddIfcsEL9AxAqdn4derUwcGDBxEZGYmAgAAEBgaKPmYiorJGTmfqUrHZG4ncs/HHjRsH\nX19fNGjQANbW1jAx4SQPEVFBSqrZP3v2DLNmzcLff/8Na2trBAYG5poBPnr0KL766ivodDo4OTnh\nk08+gUqlyneb/D+8Ecg9Gx8Axo4dC19fX6jVauzevRvTpk2TNC4iorKmpK7G37JlCxwdHREREYGB\nAwdi9erVes+npqYiKCgIa9asQWRkJOrUqYOUlJQCt8kz+2JSYjY+ALRp00a4Ep+IiOQjLi4O77//\nPgDg7bffztXsz507B0dHRwQGBuLOnTvw9PQs9NovZuPLBLPxiYjkbfKGnZLXWTHSo8DnIyMjsWnT\nJr1lVapUwYIFC9C4cWNotVo4Ozvj2LFjwvPR0dEIDAzE7t27Ub58efj4+GDZsmVo2LBhvvvhmb1M\nMBufiEjejHF1vaenZ65rrSZOnAiNRgMA0Gg0qFixot7zdnZ2eOONN1CtWjUAQLt27XDlyhU2ezIM\nqdn1muOnRNdbd+mo+Gz8+0/EZdHXss3JNHiYmi6qvpqNVZHqpb4+SU81ouprVLQGYORs/PMXRdUC\ngFXL5kj/7ZL4+jecJGfpP9m9R3S97cB+krPuNTGxouutO3dA2uk40fXl27dF6tHCPzJ8waZbZ9ll\n3cslG1+r0xZeZABt2rTB0aNH0aJFCxw7dgxt27bVe97JyQm///47kpOTUbFiRZw/fx5eXl4FbpPN\nnoiISISS+tB76NChmD17NoYOHQozMzMsXboUALBhwwbUq1cPPXr0wIwZM4TP9Xv37g1HR8cCt8lm\nX0yxsbGYOnUqHBwcAORk2Lu7uwtfixswYADatGmDTz75BEBONv5PP/2E0NBQYRuTJk1Cp06dCvxs\nPiMjAy4uLhg5cqTwF5yYmCj8pY8dO1aoHTduHDQaDebNm4fFixcDAOLj49GiRQuYmJhg9OjRcHZ2\nBgB8//33CA8Px7Zt2wz3ohARlUIldYmblZUVVqxYkWv5yJEjhT/37dsXffv2Fb1NfvXOAJSYjQ8A\nly9fxo4dOxQdFEFEVFJ4IxwSKCUbPyUlBcHBwZg7d24Rj5SIqGxhNn4Zp7Rs/OfPn+Pjjz/GnDlz\nYG1tXcSjJiIqW5Tc7PmZvQEoLRv/0qVLSEhIgJ+fHzIyMnDjxg189tln+PjjjyUfOxFRWSGnG9tI\nxWZvJHLOxm/RooUwE5CYmIjp06ez0RMRFUJOZ+pScRrfCJSQjU9ERNJooZP8kAue2ReTUrPxX6hb\nt66wDSIiyp+Sz+yZjS8TzMYnIpK34SvDJa8TPmm4EUYiHc/sZUIJ2fhS42ylRnQqPS5Xatxscpq4\n8VcubynLeqnxvWlnz4mqL9+utehoXSAnXldqfKzU7UuN430c+Z3oejvPAZLjgY1+vPG/ia9v9UaZ\nictV8rkxmz0REZEIvBqfiIiolFPymT2vxi+m2NhYdOrUCWq1Gmq1Gl5eXnrT8QMGDMDChQuFn8PD\nw4Xvy78wadIkREREFLifjIwMdO7cGd98842wLDExEU2aNMHatWv1aseNGwe1Wo1r164J43rjjTfg\n4+MDtVqNn3/+GZcvX0bXrl2F5/ft21ecl4GIqNTTFeE/ueCZvQG8HKqTmZmJ3r17Y8CAAbh+/bpe\nNr6NjQ18fHxw+PBhREZGwtPTs0jZ+KNGjYKJSc77tBfZ+C9uhPMiG79q1apCNj6Qc7X++vXrYWFh\nASAnqGfkyJEYNWqUsV4WIqJSRU5Z91LxzN7AlJKNf/HiRfz888/w8fHB3LlzhRv1EBFR3pQcl8tm\nbwBKy8YHcq7+/+ijj7B582bY29vjq6++KsKRExGREnAa3wCUlo0PAK6urqhYsaLw50WLFok/YCKi\nMohX41Mucs7GB4DRo0dj/vz5aNGiBU6ePAknJydJ4yIiKmvkNC0vFafxjUAJ2fh+fn7w9/eHWq3G\nr7/+igkTJkgaFxFRWaPkz+x5Zl9MSs3Gd3JywtatWwvdPxER5VDy1fjMxpcJZuMTEclbv8B1ktfZ\nM3uMEUYiHc/sZaJUZuP/fFx0vY1zF8nbl5rlXtay8Y19vFLrxea5l2/fFmlnfhVVCwDl32wDzamz\nouutO7aTnC0vNtcfyMn2f3b1d9H1lk0dJY9f8r0DJI5f6Vn6xqLkc2M2eyIiIhEU3OvZ7ImIiMRQ\n8mf2vBq/mJSajf/3339j/Pjx8PHxwZAhQ/Dnn38W52UgIir1eDV+GafEbHxfX1+4u7ujT58+OHXq\nFG7duoV69eoZ6yUiIlI8ntmTQCnZ+L/++iuSkpLw3nvv4fvvv0f79u2LeMRERGWDks/s2ewNQInZ\n+Hfv3kXFihWxceNG1KpVC+vWSf9KCRFRWaLTSX/IBafxDUCJ2fh2dnZCCI+Li0uu8RMRkT4lT+Oz\n2RuJ3LPx27Zti6NHj2LgwIE4c+YMHBwcJI2LiKiskdO0vFRs9kaQXzb+kiVLcP/+fdSqVUv0tvLL\nxh8wYIBeY3d3d8eCBQsQHByM27dvF7rd2bNnY968edi6dStsbGywdOlS0WMiIiqLfvab+KqHUGRs\n9sWk1Gz8OnXqYMOGDYXun4iIlI/Z+DLBbHwiIjIWNnsSTWp2/cXEJNH1zevWwN8acdnvAFDF2lJ2\n2e+Pt+0UVW/n7QEAeLrvoKj6in1yZnb+OXy0kMr/H0+PnIs+U48WPnMEADbdOgMANMdPiaq37tIx\np15knrt1x3YApL2eUn/XlF5/73Gq6Pradjai78MA5NyLwdj1D/5JE11fvUJ5yfVyycZXMn71joiI\nqJRjsyciIirlJDX7jIwM4SKwvEyfPh2DBg0S0tzESExMhJeXFwDgzJkzuHr1qpQhlbh79+7lutjN\nEEri2F8eu1qtlvT3REREymXQM/sTJ04gKioKjRs3LtL6UVFRePDggSGHZHCnTp3Cr7+Kv9e2WCVx\n7MYaOxERyVuhX73TaDSYOXMmnj59Ktwo5dq1a1i8eDGAnCQ2f39/LF26FKmpqRg/fjyCgoLw8ccf\n459//sGDBw8wbNgwDBs2DGq1Gn5+fmjcuDG2bNmCR48e4d133wUAXLx4Eb/88gsuXboEBwcH1K5d\nG0DOXeXWrFkDExMTPHz4EN7e3vDx8cHp06exatUq6HQ6aDQaLF26FKdPn8bt27cxe/ZsPH/+HAMH\nDsSXX34JX19f1KpVC4mJiejbty+uX7+Oy5cvw9nZGdOnT8/zeC5fvox169bBzMwMiYmJ6NOnD8aO\nHYu1a9fi2bNnaN26NXr06CG8Tm5ubmjTpg3++OMPVKlSBStXroRWq8Unn3yChIQEaLVaTJ06FU5O\nTvDy8sKyZctgamqKadOmYf78+fke+9q1a2FmZoa//voLQ4YMwalTp3D16lWMGDECw4YNQ0xMDL78\n8ktYWFgIY79y5UqhYweAr776Co8ePUJ6ejqCg4Nhb29vqN8rIiKSkUKb/datW+Ho6Ihp06bh/Pnz\niI2Nxfz58+Hv7w8HBwdERkbim2++gZ+fHw4dOoSQkBBcunQJffv2hZubG5KSkqBWqwv9+ljz5s3R\ntWtX9OnTR2h2LyQlJWH37t3QarVwd3dH7969cf36dQQFBaFGjRpYs2YNfvjhB6jVanh4eGDmzJn4\n5Zdf0KFDB1hYWODOnTtYv349nj17hh49euDYsWOwsrJC9+7dMX369DyP56233sK9e/cQHR2NzMxM\ndO3aFePHj8fYsWNx69YtvUYPAHfu3MGmTZtQq1YtDBkyBL/99hsuX76MSpUqwd/fHykpKRg+fDj2\n7t2LgIAAIT//888/R7NmzfI99r/++gu7d+/GpUuXMGXKFBw6dAhJSUmYOHEihg4divnz52PLli2o\nUaMGNm3ahJCQEDg7Oxc69o0bN6Jbt24YMGAAVq5ciR9++AFjxowR+3tDREQKUmizv337tpDf3rJl\nS5QrVw43b94U7tGelZWFBg0a6K1TtWpVbNq0CQcPHoSNjQ2ys7NzbVfKN/5at24Nc3NzAMBrr72G\nP//8EzVq1MBnn32G8uXLIykpCW3atIGNjQ3efPNNHD9+HDt37sSECRMAAPb29qhQoQLMzc1RtWpV\nIY1OpVIBQL7H4+joiHLlyqFcuXKF5s1XqlRJSMarVasWMjIy8PvvvyMuLg4XLlwAAGRnZyM5ORkt\nWrRAhQoVYGZmhmbNmhW43ddeew1mZmaoUKEC6tWrB3Nzc9ja2iIjIwMpKSmwsbFBjRo1AABvvvkm\ngoOD4ezsLGrszZs3B5Dz9/Xo0aMCx0FERMpVaLNv3Lgx4uPj0bNnT1y+fBnZ2dlo2LAhAgMDUbt2\nbcTFxeHhw4d666xfvx6tWrXCsGHDcOrUKeGWrObm5nj48CEaN26My5cvC03qBZVKleebgCtXruD5\n8+fIzMzEjRs3UL9+fUyYMAGHDh2CjY0NZs+eLazn5eWFdevWISUlBU2bNkViYqLQ1POT3/HktZ6J\niQm0Wm2u5XnVNmrUCDVr1sS4cePw7NkzhISEwM7ODj/88AOsra2h1Wrxww8/oHfv3vkee0Fjr1Sp\nElJTU/HgwQNUr14dp0+fFt6oSBk7ERGVboU2+6FDh+Kjjz7C0KFD0ahRI5iZmcHPzw+zZ89GdnY2\nVCoVPvvsM711unfvjsWLF2Pfvn2oUKECTE1NkZmZiREjRmDhwoWoXbs2qlevnmtfLVu2xBdffIG6\ndTvFELsAACAASURBVOsiKipKuC97dnY2xowZg8ePH2P8+PGoXLky+vfvDx8fH1hZWaFq1arCxW0t\nW7ZEQkICfHx8RL8IeR1PfhfLOTo6IiQkBE5OTtBqtUhLS4O3t3eetUOGDMG8efMwfPhwpKamYtiw\nYbh//z6WL1+OzZs3Q6fTYdiwYXjjjTfyPfaCqFQqLF68GJMmTYJKpYKtrS2WLFmC69evFzp2IiIq\nO2SfoBcbG4utW7eKvgWrVqvF0KFDERoaChsbGyOPrmxhgl7B9UzQy6eeCXqF1jNBr+B6JugVX6lq\n9nfu3MHEiRPh4eGB//3vfyUwOiIiIvmTfbMnIiKi4mFcLhERUSnHZk9ERFTKsdkTERGVcmz2RERE\npRybPRERUSnHZk9ERFTKsdkTERGVcmz2RPm4fPlynst//PHHEh4JEVHxsNlTkdy5cwcXLlxAUpL4\nSNyXnT2bO2r1+PHjedauXr26SPv4r/zud3D+/Pk8lwcEBAh/HjlypPDnb7/9Nt99XL16FevXr8fy\n5cuxYcMG4Y6HecnIyEB4eDgiIyORmZkpLN+6dWuB2//zzz+RmZmJVatW4auvvkJ6enq+9S9bt25d\ngc+/+DvRarXYvHkz5s2bhy1btuD58+d51j958gTnz5+HTqfDzp078emnnyIiIiLPu1wa0suvVUGe\nPXsmuhYA/v77b9G1Wq0WSUlJkm4slZycLOlun2K2FxAQgGXLliElJUVYvmrVqjzrtVotfvzxR8TG\nxuLJkyfw9fXF3LlzRd/xcsmSJQU+v3//fgBAWloaAgMDMXLkSHzxxRfQaPKO3r1z5w6OHj2KZ8+e\nYcWKFfjggw8QFBRUYNRwYmIiQkNDsWrVKuFB4jBBjyRJTEzE1KlTYWZmhipVquDevXuwsrLCsmXL\n8ry5UX4GDx6MHTt26C1777330LZtW0yaNAkA8PDhQ8yYMQOVKlXC8uXLc22joH/oEydOzLVsxIgR\nQqOeNWsWgoKCci1/mVqtRlhYWIF//u94Lly4gC5dusDa2hoajQbHjx/H66+/jqlTp+aqnzJlCurX\nr4/s7GycPn0aoaGhsLW1zXc8S5cuxfnz55Gamopq1aqhWbNmsLa2xtWrV7F06dJc9dOnTxfufqjT\n6RAbG4uOHTsK28rv9QkMDIRGo0GPHj1w6tQpPHv2DJ988kmu+tGjR2PIkCE4d+4cnjx5gu7du+PM\nmTN49OhRntuX6siRI1i0aBHKlSuHadOmoU+fPnrj/K8bN24gODgYtra2cHd3x7x582BiYoKPP/4Y\n3bt3z1X/xx9/6P08e/ZsBAYGAsi5E+Z/zZ07F/7+/jh//jxmzpwJOzs7aDQa+Pv7o1WrVrnqo6Ki\ncP/+fXTv3h0zZsyAhYWF8Fq+9dZbueq3bduW72uR18223n//fbi6uiI7OxsRERFYu3Yt6tSpk+/r\nM2fOHAA5/64eP34Mb29vWFtbIzo6GmvWrMlVP2TIEOHPOp0ON2/ehIODA4C835C+2O/HH38Me3t7\nuLq64uTJkzh37lyevw/Dhg3DlClTsGfPHtSsWRMuLi44c+YMjh8/jrVr1+b7OnTt2hVVq1bNc5yU\nv0Lvekf0soCAAPj6+qJdu3bCspiYGHz66aeS3mXn9R5z/fr1CAoKwujRo+Hh4YHg4GCMGzcOnp6e\neW7j5X/wAJCeno5169ahTp06eTb7l/f5119/FTgWQP82wfn9+WUnTpxARESE3jK1Wg0vL688m31y\ncrLwJubgwYMYP348Nm7cmO94zpw5g61bt0Kj0cDd3R1ff/21sI+8ODo64ujRo5g8eTJMTExw69at\nfO/Q+LILFy5g8+bNAIBu3brlu/3MzEy4urri22+/Fd789OzZM9//+arVamRlZekt0+l0UKlUeTaP\nNWvWYPfu3dBqtZgyZQoyMjLw7rvv5vv6fPLJJ5gyZQru3r2LyZMn48CBA7CwsMD777+fZ7MfOXIk\nLC0tUb16deh0Ovzxxx9YsGABVCpVns0yMTERALBs2TKsW7cODRo0QFJSEmbMmIHw8PBc9REREQgL\nC8P48eMREhKChg0bIikpCRMmTMiz2d+6dQs//fQT+vfvn+fx/VdmZqbw99msWTNMmDABYWFh+b4+\nCQkJiIiIQGZmJtzd3YV/V/m9yfDx8UFUVBQ+/vhjWFlZYcaMGaLexCUkJAh3Qm3cuDEOHsz7hk+m\npqbo0KED1qxZg0WLFgnH8WKGIC+WlpZ5/tumwrHZkyTJycl6jR4AOnfuXOgU8X/l1TBNTEwwbdo0\nTJgwAbNmzcKCBQvybfSA/jv6uLg4zJs3Dz4+Phg3blyxxwLkNKKsrCzodLpcf85Ldvb/tXfvcVGU\n+x/APys3L2AkGCFgoiUEJywqCvASZoQiIAiCgFhmmiZZSKARGmJJIqQe7SLnYBkogoQ3EDTRNE9q\nSsc0fkogXgBBFJCbwALP7w9iD7gzsCvQMs73/Xrxei2znx2+IPLdmXnmeZpRVFQEY2Nj2baioiIM\nGMB9tUwqlaKiogLDhg2Do6MjSkpKEBwcLNcQ27W2tqKkpAQjRoyQLQxVXV3Ne6r6nXfewdNPP43E\nxESsXr0aQ4cOhY2NDe/P4ebNmzh8+DB0dHRk30dZWRkaGrhXI1RXV8fvv/8Oa2tr/Prrr3jxxRdx\n7tw53u83ODgYH3/8MbZs2QI1NTXeOtppaGjgkUceAdB2KWfu3LkwNDTk/fdqbW2VfX+nT5+Gnp6e\nrE4uqampWLVqFWbPng17e3veMzb3U1NTw6hRowAABgYGvKfyNTQ0MHjwYAwZMgQmJiayPF/9K1as\nwJUrVzBx4kRYWVl1W0dLSwsuX74MMzMzWFtbY+HChVi0aBHq6/lXlDt37hyef/55bNu2DUBbY+b7\n/XFxccGYMWMQHR2N5cuXQ0tLC0ZGRrz7vnr1Kr799luoq6sjNzcXFhYWuHDhAu/vs46ODjIzMzFp\n0iTs2bMHDg4O+OmnnzBo0CC5bPtZGH19fRw4cAAWFhaynyPXWRgij5o9UQrfH06+P3je3t5yf9wY\nY7hy5Ypc9urVqwgKCsKLL76I8PBwhIaGoqSkBO+//36XDTM2Nha//PILYmJiYGFhwVu7IkfnHRUX\nF8PJyUlW8+uvv97la8PCwrBkyRJIpVJoa2ujtrYWmpqaiIiI4MwvXboUfn5++P7776Gvr4833ngD\n9+7dQ3Z2Nmc+JCQEgYGBSElJwbhx4wAAixYtwsKFC3m/h0mTJsHU1BQffvghqquru/x+Q0NDcfHi\nRbS0tODHH3/EzJkz4ePjIztKu19ERATCw8NRUVGBb775Btra2hg1ahTWrFnDmR83bhzc3Nxw+fJl\nvPbaa13WAgBGRkZYu3Ytli5dCm1tbWzevBlvvfUW7/dhamqKsLAwREZGysZbbN26Ve4MUDs9PT1s\n2LABn3/+OS5cuNBtPbW1tfDw8EB9fT1SUlLg6uqKqKgojBgxgjPv4OCARYsWYezYsVi4cCEmTJiA\nEydOyC6lcPn888+7bNYdhYeHY82aNfjiiy+gr6+PadOmQSqV4rPPPuPMR0ZGIjY2FtbW1rKao6Ki\nEBoayvs1LCwssG7dOoSFhXUaF8Dlm2++wcWLFzFq1ChcvnwZJiYmiIyM5P39X7NmDaKjo5GTk4Pi\n4mLo6uri+eef5/z9WblypexxxzMRfGdhCAdGiBJcXFzYiRMnOn0cP36cubq6cuaLioo4P/Lz8+Wy\nkydPZseOHZN9LpVKWWRkJPP29ubc9x9//MFcXV1ZdHQ0a2pq6rZ2S0tLZm9vz+zt7Ts9/sc//qHg\nd6+YmpoaVlpaympqajpt37lzp0Kvv337tlJ5RfZfV1fHDh069ED1dJdvaGhgpaWlrKGhoUf7v59U\nKmWpqamsvr5etq28vJytWbOGM9/S0sIOHz7caduePXs6vZ5Pamoq8/Pz6zbX2NjIzp8/zy5fvswa\nGxvZjh07uvzdO336NIuJiWEff/wxW79+PTt69ChvtuPvviL48i0tLb2+/5aWFnb+/PkHqqe38owx\nlp2d3enz9PR0pfchVtTsiVKWL1/O+6GI69evs7Vr1zJbW1u558rLyzlfk5WVxbnd0tKS2djYsFmz\nZjFvb2/m7e0te9wbpFIpS05OZowxFhQUxObMmcMCAgLYtWvXHmh/c+bMEXU+MjJSqdeLLd/f//1U\nmc/OzmYxMTHMwcGBxcTEsJiYGBYdHc2cnJyU+ppiRqfxiVK4Tr8D3Z8W/+mnn5CQkICcnBwsWLAA\ne/bs4czMnDkTAPDnn3/iqaeeAgDk5eXB0dFRLp+VlaVs+fjPf/4DOzs7rFu3DpWVlZBIJFi2bJns\n+m5H69atk10+KCkpwaefforTp0/jyy+/7HRbnqKYkje+PGz5vLw8pV4vtjzrMC7kfpqamqLOm5ub\no6qqClpaWrJr9BKJBM7OznKvJdyo2ROlxMbGKpWPj49HWloazMzMMG/ePLS2tvJeY967d6+s2UdG\nRsquxZ05c4Yzb2RkhOLiYqSlpaG4uBgjRoyAu7t7pwFyHX355Zf4888/YWdnh7NnzyIwMBBnz57F\nl19+ifDwcLn8pUuXZDWoq6tj9OjRGD16tNwtg4pSZJzAw5wvKyvjHfnNdZeA2PLnz5+Hk5OT7A4F\n4H93Kxw5ckTUeUNDQ7i7u8PNzY13/A7pGjV7opSuRuNyiY+Ph7OzMzw8PGBmZob4+HjebMd3+HyP\nO/r9998RFhYGPz8/PPvss7h27RreeecdfPrpp7IBbB398ssv+PbbbwEAWlpamDBhAuzs7HhH/Hcc\ndLhs2TLZY21tbd7vgfCTSqUoLy+nPI9x48YpdDeAWPNA28RQcXFxGDhwoGwb32RcpDNq9qRPZWdn\nIysrC59++ikaGhpw79491NTUQEdHRy6r7H3tGzduxDfffCMbWTx+/HhMnDgRK1eulN1adL/2W77m\nzp0r+5yrFqDtTUZtbS20tbVlk6bU1tY+8Cxo/f00e1/n+eY/4CO2POleeno6Tpw4wXl7HukanQ8h\nfUpTUxMuLi7Yvn07oqOjMXHiRLi5ueG9996Ty1ZVVeHnn3/GiRMnOj2+e/cu576bmprkbnsyMTHh\nvW9YKpXKnpsyZYpsH3zTwfr6+iIwMBCXLl1CXV0dLl26hKVLl/JOMtPVNLdA26x9Ys4bGBh0mb+f\n2PJcl5Io35mxsXGno3qiOJoul/ztmpubcfToUbl7rdun82x39+5dqKmpQVtbm3Nebj8/P9lMb+0Y\nY5g1axZSUlLk8omJifjtt98QHh6ORx55BNXV1bKpTvlmfWsfWFhcXAxDQ0O4uLjg1q1bWLBggVz2\nvffeQ3NzMz777DPo6up2+3MQW76kpIT3Oa571cWWDwgIkNvWfg2b615yseUB4O2338bNmzcxduxY\nAG1n/XpjamYxoNP4pE/dvHkT//73vzFs2DC8+uqrCAwMRHNzMz755BO5rL+/Pz766CPs3r0bR48e\nxapVqzB06FCEhIRw7tvOzg7r169HUFAQBgwYgNbWVnzxxRewt7fnzPv5+UEikcDf3x9VVVXQ1taG\nr69vl3NrT5o0CZMmTcLvv/+OhIQEREdHyybXud+mTZuQnp6OgIAAhISEYPz48V3+bMSWnzx5MoyM\njDB8+HAA/zvNzzddrtjygwcPxvXr1zF16lRMmTIFWlpachkx54G2Zk8eDB3Zkz41Z84cuLi44O7d\nu4iLi8OmTZvw+OOPIzQ0VG6k8ty5c7FixQqYm5tj2rRpiI6OxhNPPIH58+dz/nFsbm7Gxo0bsX//\nfujq6uLu3btwcnJCcHCwQtOxtu8jKyuL8xaepqYmpKenY8eOHdDQ0EBtbS2Sk5O7PY1YUFAAb29v\nhQcRiSV/6NAhZGRkoLGxEU5OTnB0dOzy2qvY8kDbpayDBw/iyJEjGD58OFxcXGBra8s7bkVs+dra\nWmzZsgUFBQUYNWoUFi9erNBZJQKaQY/0LV9fX9ljDw8P2eM33nhDLuvv788YY6y0tJS98sorsu0+\nPj7dfp07d+4oNIteu7KyMrZx40Y2YcIEtmDBAs6Mvb09W7t2LSssLGSMMfbWW291u9+UlBQ2efJk\nlpaWplAdYsszxlh1dTVLTk5mCxcuZCEhIez48eOU51BUVMSWLl3KJkyYQPm/BAYGsu3bt7Pc3Fz2\n7bffsoULFyq0b0KT6pA+1vEIe8iQIbLHXIPi2ufdP3HiBGxtbQG0Darjmys8JiaG9wggKCiIc/uZ\nM2eQkJCA//u//8OAAQOwa9cuGBoacmbnzp2L/fv3o7i4GJ6ent2ORp8/fz4YY0hMTMTjjz/eZVaM\n+XY6Ojrw8vLCk08+iW3btmHFihVdnjkQW/7KlStIT09HdnY2TE1NeeeWF2O+srJSNkD26aeffqCJ\ntcSKmj3pUzdu3EBsbCwYY50ety8X2pGtrS18fHxQWlqKr776CtevX8fq1atl65jfb/To0UrV4uHh\ngdGjR8PHxwcvv/wyFixYwNvogbbrg2+//TbOnDmDlJQUXLx4EdHR0XBzc5MNEOrIwcEBfn5+ctvL\nyso4R2aLLQ+0TVR04MABHD9+HBYWFvDy8pKt4Cf2fFxcHA4dOgQ9PT04Oztjx44dXZ72F1seABob\nG1FeXo7hw4fj9u3bvAtwEXl0zZ70qbS0NN7n3N3d5bYVFBRAW1sbBgYGuH79epcrpKWmpspm3FPE\nJ598gpycHNlEOlFRUUotzVtdXY29e/ciNTWVc7rf+506dQqJiYnIycnByZMnRZ9vHxfh7OyMyZMn\ndxqQxbVMqdjy5ubmGDlyJB599FEAneeX4BqzIrY8AJw8eRIrV66EtrY26urqEBkZKTsLSLpGzZ6o\n1LvvvostW7Y80GsDAgKUXt6yoaEBBw8eREpKCv7880988MEHmDZtWq8N8qmvr0daWhp27tyJ8vJy\nhIeHw9HRkXNucLHlO85PIJFIOo1O5/p3FFu+uLhYbhvQ9js7ZswY0ec7qqiowLBhw7rMkPv8zWME\nCOmkfVDeg/Dy8mKFhYXsypUrch+KyM/PZ2vXrlV4AFF3Vq9ezaZNm8ZiY2NZYWFhtwP6xJbn0tTU\nxPbv3095Dl2tECnW/M6dO9mMGTPY1KlTZR9EMXTNnqiUsourdFRYWIiVK1fKDZzjO3K6f2Y9ExMT\nBAUF9dqUpufOnYOlpSXGjRuHkSNHdvu9iS3f0a1bt5CUlITU1FSYm5tj+vTplP+LIitEijW/fft2\nbN26FY888kiX+yTyqNkTwTI3N1fqNL6Tk5Pc6VTWxapcytqzZw9ycnKQkpKCqKgoMMZQUFDAe0pS\nbHlA/m6IpKSkLgdJiimvzAqRYswDgJmZGQwNDRWeR4N0oLJzCoQwxubMmfPAr+3JJYCOWltbe2U/\njDFWU1PD6uvrWU1NDUtMTGTu7u7M3d2d8owxd3d3tmzZMnby5EnW0tLS7Wl/seXt7e3ZZ599xi5d\nusQYY2z+/PmUv09SUhJ75ZVX2Jw5c5i/v3+P/n6IDR3Zkz7FOqxVzaUnp+M2btwot62yshIpKSmc\nc9fX1NRg9+7dGDp0KNzd3TFgwABcvnwZq1at6nZRF0UkJCQgPj4e6urqCA8Ph6+vL3x9fZGbm0t5\nAFZWVsjJycHx48dhYGDQ7Wl/seWVWSFSjHkA2LVrFzZs2NBlhvBQ9bsN8nD7u955nz9/noWEhDA7\nOzsWERHBmXnzzTdZTEwMCw4OZv/85z/Zzp07mb29Pdu3b1+v1ODt7c0aGxvZnTt3FBqsJrY8Y4zd\nu3eP/fDDD2z27NnshRdeYImJiayyspLy97l69SqLjo5mDg4OLDAwkPJ/eeedd1hLS0u3+yPyqNmT\nPtWXzb6xsZH98MMPbObMmWz27NnMxcWF3bt3jzc/a9YsxljbaXtHR0f25ptvstu3b/daPR2/14CA\nAMp3Iz8/n0VFRSl8N4TY8owxJpVK2aFDhxhjbSPRxZ6fN28emz59Ovvggw9YUFAQCwoK6nafpA01\ne9KnbG1tZf8p7//oKWXnru94jd/FxYU1NDT0uIaOOjY/Rd7kiC3Pp31Ng8WLF1O+C8r+jB/G/OnT\np+U+iGLomj3pU4899hi8vb37ZN/Kzl3f8Zqprq6uQktqKiM/Px/Lli0DY0z2uB3Xmttiy/PR0NAA\n0DZDIeX5dff7LYa8jY1Np88vXLig1D7FjJo96VM6Ojpy/0F7i7Jz1//xxx/w8fGRNaf2x3zriytr\nw4YNssc+Pj6UV5Kycy5QnvKZmZl45plnlNqvWFGzJ33qlVde6fOvYWNjAxsbG1RXV2Pfvn0ICQnh\nnJhj3759fV4H5QnpO6WlpZ1WWFRmbQyxo2ZP+pSZmRnvcp7jx4/v8f5//vln2NvbQyKRoKSkBCNH\njuSdgcvAwADZ2dkYOnQoXn75ZQDA7du3sWbNmk5HqYT0R0I4zd5X+by8PJSVlWH9+vX48MMPAbQt\nkx0bG4u9e/cqtV+xomZP+lR6ejrvcz1t9jt27MC+ffvw7LPPQltbGwCwZcsW3Lx5k3OcQHBwMNTU\n1FBeXo78/HwYGxsjLCwMAQEBPaqD9A5l51x42PJJSUldXg5pb3JizFdXVyMjIwN37tyR/U2RSCTw\n9fXlfT25z986HJCQXuTp6Sk3or62tpZ5eHhw5ttndmtsbGTTp09n7u7uLD8/v8/rJF1T9ra9hzUf\nGBjIFi1apNB9+GLMM8bYr7/+2unzkpIShV8rdgNU/WaDPNwCAgJ4P3pq4MCBciPqhwwZgiFDhnDm\n24/+NTU10draivj4+G6X0iR9r7a2lvIANm3aBGdnZwQEBPBe+hJzHgBWr16Ny5cvAwCysrIwb948\nhV5H6DQ+6WODBw/G9evXMXXqVEyZMqVXb3fT0NCQW9e6oqICLS0t3b5WT0+v19awJz3TH0Z195e8\ns7MzzM3N4e3tjYEDB8q28zVDseVjY2MRFhYGPT09qKurIzExkTNH5FGzJ33q66+/RlVVFQ4ePIiY\nmBgMHz4cLi4usLW17fG+Fy9ejLfeegszZsyAiYkJbt68id27d8tdG2zXW/eFkweza9cuuW2MMVRU\nVFD+L7t378ZXX32Fjz/+GDNmzODNiTXP/hq019TUBA0NDVr9TgnU7Emf09XVxezZszF79mwUFxcj\nOjoay5cvx/Hjx3u03xdeeAGbNm3C3r17cezYMRgZGWHz5s0wMjLizPf2feFEOeXl5ZzbPTw8KA9g\n/vz5YIwhMTGx0+1lfMSWB4D3338fUVFReOaZZ5CZmQlfX98uBwGTDlQxUICIT0FBAdu0aRObMWMG\n++CDD1h2dnaP91lcXCz7KCkpYXfu3FHq9TU1NWz79u1s6tSpPa6FPLj09HTKM8YSEhI4t5eWllL+\nLzU1NYwxJhvUV1xczJslnUkYU/LmR0KUEBcXh0OHDkFPTw/Ozs6YMmUKBg0a1Cv79vb27nT9s66u\nDk1NTVi3bh3GjRvH+7r8/HwkJCQgMzMTjo6O8PT0hJWVVa/URJTn6emJ3bt3U/4+p06dQmJiInJy\ncnDy5EnKA/j1118RERGBlpYWODk5YcSIEfDy8up23wR0ZE/6lpmZGXvttdfYrFmz2KxZs5i3t7fs\noy9cu3aN+fr6cj6XmZnJ5syZw3x8fFhycvIDrdRGeh/frZJizNfV1bGEhATm7OzMbGxs2P79+1lj\nYyPl/+Lr68sqKyuZv78/a2hokN1OS7pH1+xJnzpy5Mjf+vVGjhzJO9o5NDQUAQEBePPNN/Hoo4/i\n0KFDf2tthJuQRsv3ZT4yMhKnTp3ClClTsHnzZqxZswbTp0/n3Y/Y8gAwYMAA6OrqQiKRQEtLi/c2\nWyKPmj3pU4WFhbzP8Q2k64mWlhbU1NRwPpeVlYW0tDT4+flh7NixqKys7PWvT/jxzZhYVVVFeQDn\nzp2DpaUlxo0b1+WbVrHmgbY38zExMaiqqsLWrVsxYsSIbl9D2tA1e9KnVqxYwbldKpVi/fr1Pdr3\n/bc2NTU1ITs7G9bW1ggMDOzytb/88guSk5Nx/vx5vP766wgNDe1RLYT0hpycHKSkpODcuXNgjOHr\nr7/ucuInseWbm5uRkpKCvLw8jBkzBrNmzYKmpiZvnvwPNXuiEsoOauKyefPmTp9raWnB0tISdnZ2\nnHmuNx6VlZU4e/Yszp4926NaSPe47jtvx7WWgdjyQNvsempqamhpacG+fftk/0d++OEHyqPtPvsL\nFy6gsbFRtu3FF1/kzJLO6DQ+UYneeI+5ZMkSAMCNGzdQWVkJAwMDGBgY8OYvXryIhoYGuLq64rnn\nnpPV4Ofn1+NaSPfuv++8/Q8236yKYssnJCQgPj4e6urqCA8Ph6+vL3x9fZGbm0v5vyxZsgSVlZUw\nNDQEYwwSiYSavYJobnyiEsoOauJSVFQET09PhISEYOvWrVi0aBH8/Pxw69Ytzvz+/fuxZcsWNDY2\nYuvWrfjvf/+LkSNHYsKECT2uhXTv1VdfxcWLF3Hz5k1YW1sjOTkZycnJMDY2pjyAAwcOIDMzE0lJ\nSfjuu+9k2y0sLCj/lzt37mDHjh2IiYlBbGwszXypBDqyJ30qKChIrrEzxnDjxo0e7zsqKgrLly/H\nCy+8INt28uRJrF69Wu4Uf7uxY8ciODgYQNs9uzExMSgtLUVycnKP6yFdi4iIwHvvvYeqqiq8++67\nSEtLw7BhwzB//nzOqVLFltfU1ISmpiaGDRsGqVTa7c9TbHkAMDU1RVlZWZdn8Ag3avakT/FNS9sb\n09VWVFR0avQAYG9vj7i4uC5fV1tbi8OHD+PAgQO4d+8eXF1de1wL6Z6GhoZsPMX27dsxatQoAG2L\nJVG+M2Uvc4kln5OTAwcHh06LXym6Yp7YUbMnfcrGxqbP9q2uzv3r29rayrk9IyMDGRkZKCkpgaOj\nIyIiInhPqZLe1/EMT8cR1Hz/XmLLK7tQk9jyQNvts+TB0Gh8Iliurq4ICQnptI0xhvXr12PvM6Iy\n9QAACA5JREFU3r1yeXNzc4wePRrm5uYAOv8xpmt/fc/Ozg62trZgjOHUqVOyx6dPn+acHlVs+TNn\nzvD+7LjeNIstzyUlJYWmy1UQNXsiWHz38Dc2NiI2NlZue2/8cSEPrr81j/6WJ8o7cOBAt7PukTbU\n7Ilgvf/++7Jla+Pj4zFv3jwAQEBAALZv367K0gghfeDo0aNwcHCQfZ6RkYFp06apsCLhoGv2RLAq\nKipkj48dOyZr9oSQh8vRo0eRk5OD9PR0/PbbbwDapsbOzs6mZq8gavZEsDqelKITVIQ8vMzNzVFV\nVQUtLS2YmpoCaBtzQ6fwFUfNnghWxwF2vTFJDyGkfzI0NIS7uzvc3NwwYADNBfcgqNkTweK6dYcx\nhoKCAlWXRgjpA3FxcYiLi8PAgQNl2+g+e8XQAD0iWDTamRBxcXV1xa5duzBo0CBVlyI4dGRPBIsa\nOiHiYmxs3OmoniiOmj0hhBBBkEqlcHFxwdixY2XjdGhCLMVQsyeEECIIb7/9tqpLECwa1kgIIUQQ\nLCwscPLkSaSlpaGqqopWv1MCNXtCCCGC8NFHH8HExATXrl2Dvr4+wsLCVF2SYFCzJ4QQIghVVVXw\n9PSEuro6rK2teVcQJPKo2RNCCBGM9nk0SktLoaampuJqhIPusyeEECIIeXl5CA8PR0FBAUaPHo1V\nq1bB0tJS1WUJAjV7Qggh5CFHt94RQggRhC+++AKpqamdttF0uYqhZk8IIUQQjh07huzsbGhqaqq6\nFMGhAXqEEEIEwcLCAo2NjaouQ5DoyJ4QQoggPPXUUxg/fjz09fXBGINEIsGRI0dUXZYgULMnhBAi\nCBkZGThy5AiGDh2q6lIEh5o9IYQQQRgxYgQGDRpE1+wfADV7QgghglBaWorXXnsNJiYmAACJRIKk\npCQVVyUMdJ89IYQQQSgsLJQ7qjcyMlJRNcJCzZ4QQogguLi44OWXX4aXlxfGjh2r6nIEhZo9IYQQ\nQWhtbcWJEyeQmpqKyspKuLq6Ytq0aRgyZIiqS+v3qNkTQggRDMYYjh8/jt27d+PatWsYPHgwpk+f\nDn9/f1WX1q9RsyeEECII69atw5EjR2BjYwMvLy9YWVmhtbUVHh4e2LNnj6rL69eo2RNCCBGE5ORk\nODs7y522LyoqgrGxsYqqEgZq9oQQQgTh6tWryMrKglQqBQDcunULq1evVnFVwkBz4xNCCBGE4OBg\nAEBOTg6KiopQVVWl4oqEg5o9IYQQQRg8eDAWLlwIAwMDREVF4fbt26ouSTCo2RNCCBEEiUSC8vJy\n1NXVob6+HvX19aouSTCo2RNCCBGEJUuW4PDhw3Bzc8OUKVNga2ur6pIEgwboEUIIEYyKigrcuHED\nTzzxBHR1dVVdjmDQQjiEEEIEITExEd999x2eeuop5OfnY/HixXBzc1N1WYJAzZ4QQoggpKSkYP/+\n/dDS0sK9e/fg7+9PzV5BdM2eEEKIIOjp6UFNTQ0AMHDgQDqNrwS6Zk8IIUQQ5s2bh1u3buG5555D\nbm4umpub8eSTTwIAYmJiVFxd/0bNnhBCiCCcOXOG9zkbG5u/sRLhoWZPCCFEkC5cuIBnnnlG1WUI\nAl2zJ4QQIkiZmZmqLkEwqNkTQggRhNLS0k6fz5w5U0WVCA/dekcIIaRfy8vLQ1lZGdavX48PP/wQ\nANDS0oLY2Fjs3btXxdUJAzV7Qggh/Vp1dTUyMjJw584dpKenA2ibJ9/X11fFlQkHDdAjhBAiCH/8\n8QcsLS1VXYYg0ZE9IYSQfs3b2xsSiYTzuaSkpL+5GmGiI3tCCCH9WnFxMe9zRkZGf2MlwkXNnhBC\niCBs3rxZbtuSJUtUUInw0Gl8QgghgqCvrw8AYIwhNzcXra2tKq5IOKjZE0IIEQQfH59On8+fP19F\nlQgPNXtCCCGCUFhYKHtcXl6OkpISFVYjLNTsCSGECMLKlStlj7W0tBAaGqrCaoSFBugRQggRJKlU\nCg0NDVWXIQh0ZE8IIUQQkpKSsG3bNjQ3N4MxBg0NDWRlZam6LEGghXAIIYQIQmJiIr7//ntMnDgR\na9euxZgxY1RdkmBQsyeEECIIjz32GB577DHU1dXhpZdeQk1NjapLEgxq9oQQQgRBR0cHP/74IyQS\nCZKSklBVVaXqkgSDBugRQgjp1woLC2Fqaora2lpcv34denp62LZtGxwcHPDSSy+pujxBoGZPCCGk\nX/Py8kJKSgreffddbNmyRdXlCBKNxieEENKvmZiYwNbWFjU1NRg/fnyn537++WcVVSUsdGRPCCFE\nECIiIrBq1SpVlyFI1OwJIYQIQm1tLf71r3+hrKwMDg4OMDMzwxNPPKHqsgSBRuMTQggRhI8++gjG\nxsa4du0a9PX1ERYWpuqSBIOaPSGEEEGoqqqCp6cn1NXVYW1tTUvcKoGaPSGEEMEoKCgAAJSWlkJN\nTU3F1QgHXbMnhBAiCHl5eVi5ciUKCgpgamqKTz75BBYWFqouSxCo2RNCCOnXJk+eDIlEAgCyBXCk\nUim0tLRw8OBBFVcnDHSfPSGEkH4tMzMTjDFERETAx8cHVlZWyM3NxY4dO1RdmmBQsyeEENKvaWpq\nAgBu3LgBKysrAICFhQUKCwtVWZagULMnhBAiCDo6OtiwYQOsrKzw22+/Yfjw4aouSTDomj0hhBBB\nqK+vR1JSEq5evYoxY8Zg9uzZsqN+0jVq9oQQQshDju6zJ4QQQh5y1OwJIYSQhxw1e0IIIeQhR82e\nEEIIechRsyeEEEIecv8PAMB22Vs87i4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1e1bdfca4e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sb.heatmap(corr,mask=mask,cmap=customap,vmax=0.8,center=0,square=True,linewidth=0.4,cbar_kws={\"shrink\": 0.9})"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
